This study proposes an integrated multi-model coupling framework for ex-ante carbon assessment in new urban district planning. The framework combines investment allocation, land-use carbon estimation, and traffic emission models within a unified analytical environment to simulate spatial and economic feedbacks that drive urban carbon emissions. Compared with conventional carbon assessment approaches, which often evaluate land use and transport as independent modules, the proposed framework introduces a rule-based coupling mechanism that dynamically links investment intensity, spatial configuration, and carbon output through iterative feedback. Each sub-model exchanges parameters via a shared data layer, enabling recursive interactions among economic input, land-use change, and mobility patterns. The framework advances urban carbon modeling through three key innovations. First, it establishes an investment-carbon elasticity mechanism that quantifies how capital concentration influences spatial emission patterns. Second, it formulates a rule-based symbolic coupling algorithm that enables cross-model parameter updating during iteration. Third, it develops a feedback-controlled carbon evaluation process that transforms traditional PSS from descriptive visualization tools into predictive decision-support frameworks. Applied to a representative new urban district, the framework demonstrates effectiveness in identifying low-carbon planning strategies under varying investment-intensity scenarios. By integrating economic, spatial, and environmental dimensions into a unified analytical logic, this research provides a scalable foundation for quantitative decision-making in sustainable urban transitions and contributes a theoretical model applicable to broader regional and national carbon-neutral planning frameworks.

ABSTRACT There is a limited understanding of how port-hinterland connections via inland shipping respond to major disruptions. This study investigates how containerized inland waterway transport in the Rhine-Alpine Corridor adapted after global disruptions between 2007 and 2022. Employing panel data modelling and network analysis, the paper examines regional transport hubs and reveals how their connections responded to events such as the financial crisis, critically low water levels, and geopolitical instability. The results provide insights into the vulnerability of cargo flows during disruptive years, along with distinct shifts in network connectivity following each event. The assessment reports the degree of robustness and redundancy across the corridor, offering practical guidance to support the development of regional responses to future disruptions.

ABSTRACT Increasing attention to the environmental impacts of the transport sector has given rise to a range of studies dedicated to identifying policy instruments that can promote a shift towards more sustainable land use and transport planning. However, little is understood about the calibration of policy instruments to support this shift. This article seeks to illustrate the impacts of instrument calibration in reducing transport emissions and volumes. It does so by studying the evolution of policies for sustainable mobility in the city of Espoo (Finland) from 2013 to 2025. The empirical material highlights the significance of the calibration of policy instruments in the process of transitioning to more sustainable forms of urban mobility.

Beyond buzzwords: Evaluating the integration of accessibility goals and indicators in land use and transportation policy documents

• This paper introduces a new approach to mobility hubs through their transport supply and surrounding context. • The classification process is reproducible, making it applicable to various contexts and for different urban scalables. • The methodology re-adapts the ABC location policy to identify potential locations for Mobility hubs. • The classification system employs a range of indicators, providing a comprehensive perspective from the literature on mobility hubs from both node and place dimensions. • The proposed methodology has been tested in Milan’s first belt area, allowing for a comparative analysis of the current situation and future transformations. Multimodal Mobility Hubs have gained increasing attention as a sustainable approach to promoting environmentally friendly transportation in cities. By co-locating multiple transport services, mobility hubs offer efficient multimodal transfers and address issues such as car dependency, congestion, and unequal access to mobility. Building upon these advantages, this paper introduces a reproducible classification method that evaluates both the transport supply (Node) and the physical and functional characteristics of the surrounding context (Place). The methodology readapts the ABC location policy and the Node–Place classification model to systematically identify existing nodes that can serve as multimodal mobility hubs, combining them with comprehensive indicators derived from the mobility hubs literature. Through this approach, the paper illustrates how open and standardized datasets are used to (i) cluster and score transport nodes based on their multimodal offerings, (ii) analyze land use and urban services in their catchment areas, and (iii) compare current conditions with planned transport and land-use transformations. Additionally, this paper introduces a cross-scale approach to support the localization of potential multimodal mobility hubs, their classification, and insights into their future performance. The proposed framework is tested in Milan’s metropolitan area, where it highlights opportunities to enhance multimodality and, alternatively, provides deeper insights from applying transformations in land use and transport supply. Findings show that this approach is scalable and replicable across diverse urban contexts. Ultimately, the paper contributes to evidence-based policy by offering a tool to guide urban and transport planners in locating, selecting, and upgrading mobility hubs, facilitating more sustainable and inclusive mobility networks.

With the official opening of the Pinglu Canal, the core backbone project of the New Western Land-Sea Corridor, the demand for clean energy refueling infrastructure for inland shipping has increased sharply. Liquefied Natural Gas (LNG), as a low-carbon and efficient ship fuel, has become the main direction for the green transformation of inland shipping. However, the current site selection of LNG refueling stations along inland rivers faces problems such as single evaluation dimension, strong subjectivity in weight determination, and lack of spatial quantitative analysis. To address these issues, this paper constructs a suitability evaluation index system for LNG refueling stations along the Pinglu Canal from four dimensions: waterway and navigation conditions, market demand conditions, resource and infrastructure conditions, and safety and environmental conditions. A combination weighting model integrating Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) is established to determine the index weights, which effectively balances the subjectivity of expert judgment and the objectivity of data information. Combined with Geographic Information System (GIS) spatial analysis technology, the single-factor raster layers are superimposed and analyzed to obtain the comprehensive suitability distribution map of LNG refueling stations. The results show that the highly suitable areas for LNG refueling stations along the Pinglu Canal are mainly concentrated in the Qinzhou Port section, Luwu Town section and Xijin Reservoir area of Hengzhou, accounting for 4.2%, 2.5% and 2.0% of the total study area respectively (totaling 8.7% of the total region). Finally, 5 optimal alternative sites are proposed, which can provide scientific decision-making basis for the planning and construction of LNG refueling infrastructure along the Pinglu Canal.

Breaking the coordination deadlock of hydrogen application in inland shipping: a four-stakeholder evolutionary game analysis

How does urban land use and transportation spatial configuration affect carbon exacerbation and mitigation?

Abstract In recent years, our country’s electric ship industry has developed rapidly, and the application scale and technical level have jumped to the forefront of the world, providing important waterway transportation support for the implementation of the “double carbon” goal. Relying on the advantages of inland shipping resources, Huzhou actively promotes the development of electric ships and achieves initial results under the guidance of national and provincial policies. However, pure electric ships still face practical challenges such as insufficient endurance and imperfect charging and swapping infrastructure. Therefore, based on the actual situation in Huzhou, this paper innovatively proposes a comprehensive layout optimization method of “ship-shore-electricity” collaboration based on the systematic analysis of the applicable scenarios and layout logic of ship charging and swapping stations. By constructing a regional electricity demand model, measuring the scale of facilities, formulating power supply and expansion plans, and carrying out economic-social-environmental three-dimensional benefit assessments, a set of replicable and generalizable “Huzhou Plan” for the green transformation of inland waterway shipping has been formed, which has both theoretical value and practical guiding significance.

Integrated safety and security quantitative risk assessment for inland transportation of dangerous goods

Aviation transport system in the agricultural sector has been examined in this study. The task addressed relates to determining the factors of expedient use of air transport at certain stages of the technological process of growing agricultural crops, depending on aircraft technical parameters. The global experience in the development of agricultural aviation has been analyzed; analysis of the areas cultivated by land and air transport in Ukraine in 2013–2024 was performed. The negative impact of vehicles on the environment was revealed. Directions for improving environmental safety through the introduction of promising new technologies for environmental preservation have been determined. Basic aviation means used to protect plants from harmful objects during the growing season were analyzed. The selection of aviation means for the implementation of crop protection measures should be carried out on the basis of a preliminary scientific and economic justification, taking into account the type and scope of work. Ranges of the technological cycle duration and ranges of productivity by agricultural aviation activities based on the technical and operational characteristics of agricultural aviation means have been determined. The expediency of using aviation means under different standards of application of working substances has been clarified. Under current conditions for precision agriculture, there is a need for wider use of air transport in the process of growing agricultural crops. An innovative tool for precision agriculture are unmanned aerial vehicles that help with field spraying, control and cartography of yield data, fertilization, as well as diagnosing crops for the presence of pests and diseases. That is why the market of unmanned technologies is rapidly evolving in Ukraine, which is a promising direction in the agricultural sector

A systematic mapping of artificial intelligence (AI)-based mobile driver coaching for behavior change and road safety in land transportation has been conducted following PRISMA, resulting in nine empirical studies (n = 9). The evidence is organized through a taxonomy covering intervention goals, AI techniques, data sources, deployment patterns, outcome and engagement metrics, and privacy/dependability safeguards. Across the mapped interventions, a substantial share targets specific risky behaviors, particularly phone-related distraction, reporting relative reductions of up to 21% versus controls in controlled evaluations. Deployment designs are predominantly hybrid, combining on-device inference for timely detection with server-side components for aggregation and program features. Based on the extracted evidence, a system-oriented design framework and practical guidelines are proposed to support researchers and mobile system designers in selecting architectures and evaluation metrics for interactive driver coaching. Key limitations include heterogeneous outcome definitions and predominantly short- to medium-term follow-up, which constrain comparability and generalization across settings.

Abstract This paper introduces NeXT (NeXT-generation night-photometer), a low-cost mobile device for night sky brightness (NSB) monitoring. NeXT is based on the TSL2591 high-sensitivity, dual-channel light-to-digital sensor, with wireless communication (LoRa, WiFi, or LTE-M), and powered by solar-rechargeable batteries. Field autonomy tests show the device can operate continuously for up to four weeks without direct solar irradiance, after which it hibernates for less than one week, with automatic reactivation once re-illuminated. Two additional sensors -GPS and inclinometer- record latitude, longitude and zenithal distance of NSB measurements, enabling its installation on sea or land transport. We calibrated 20 NeXT photometers using patent-pending sky integration sphere method against IOT-EELabs TESS reference photometers, achieving calibration uncertainties of ∼0.04 mag arcsec −2 for brightness and for (Visual—Infrared) photometric measurements using twilight sky models. Validation measurements at Observatorio del Teide yielded a 50th percentile (P50) of 21.104 ± 0.039 mag T E S S arcsec −2 and 1.780 ± 0.033 mag ( V − I ) , N e X T under maximum darkness filters. NeXT is an autonomous, dual-channel NSB sensor suitable for fixed remote locations or mobile platforms, requiring no additional infrastructure. The dual-band colour capability represents a significant advancement, offering enhanced monitoring capabilities to track and discriminate artificial light pollution sources from natural background emissions.

This study examines how the allocation of export expansion across sectors affects economy-wide outcomes in Bangladesh. Using a Social Accounting Matrix (SAM) framework, we combine linkage analysis with simulation to evaluate how sectoral export growth propagates through the production network. The results show that the impact of export diversification depends critically on sectoral allocation rather than export intensity alone. While aggregate differences between scenarios are modest, reallocating export growth toward sectors with stronger intersectoral linkages generates larger economy-wide gains in GDP and labor income. In particular, sectors with low initial export shares but high network connectivity—such as agriculture, hunting, forestry, and fishing; retail trade; other community, social and personal services; and inland transport—produce stronger multiplier effects than most export-intensive sectors. These findings highlight a key distinction between export intensity and network centrality, demonstrating that sectors with limited direct export participation can play a central role in transmitting economic gains. The results provide a network-based perspective on export diversification and offer policy-relevant insights for designing strategies that promote more inclusive and efficient economic growth.

Environmental quality is an important indicator that reflects the sustainability of ecosystems and the welfare of communities in a region. The Environmental Quality Index (EQI) provides a quantitative measure of environmental quality in an area over a given period, derived from the Water Quality Index (WQI), Air Quality Index (AQI), Land Quality Index (LQI), and Marine Water Quality Index (MWQI). To date, Java Island has consistently had the lowest LQI among Indonesian islands. This study was conducted to determine the effect of access to proper drinking water, access to adequate sanitation, population density, land transportation, and the number of large and medium industries on the Environmental Quality Index (EQI) in 6 provinces on the island of Java from 2016 to 2024 using panel data regression analysis with the Fixed Effect Model (FEM) approach and Granger causality testing with 54 observations. The study found that access to safe drinking water, access to proper sanitation, population density, and the number of industries significantly affected the EQI. Land transportation did not have a significant effect on the EQI. Based on the Granger causality test, there was a reciprocal relationship between several independent variables and the EQI.

Problem, research strategy, and findings Pedestrian and bicyclist deaths now account for nearly one in five traffic fatalities in the United States. They continue to rise even as peer nations have reduced deaths dramatically. We examined 222 miles of arterial highways in Florida to understand the nature of the unique risk confronted by vulnerable road users in the United States. We found that land use decisions—particularly the siting of groceries, pharmacies, gas stations, and fast-food outlets—are strongly associated with the death and injury of vulnerable road users. These household-sustaining uses generate exposure in locations fundamentally incompatible with vulnerable road user safety, activating latent hazards embedded into infrastructure design. We discuss in this article how land use practice differs from that of Europe, and how these differences explain the differences in safety outcomes. We conclude by developing tools for estimating the magnitude of this risk during the project development process and by outlining strategies for enhancing land use and transportation practices to better account for the land use–road safety connection. Takeaway for practice Meaningful progress toward Vision Zero in the United States requires acknowledging that land use decisions—not just street design—are a primary driver of the elevated risk faced by vulnerable road users. Development codes that encourage household-sustaining uses to locate along arterial corridors create predictable and preventable exposure in environments where safety is structurally unattainable without simultaneous changes to the street’s design and function. Addressing this risk demands a shift in planning practice: revising zoning and site-planning standards to explicitly account for safety, redirecting high-risk uses away from arterial corridors, and applying analytic tools that identify and mitigate latent land use hazards during the planning and project development process.

Abstract The Energy Efficiency Design Index (EEDI) serves as a key measure of a ship’s environmental performance and an indicator of its energy efficiency. For seagoing vessels, the International Maritime Organization (IMO) used comprehensive ship data from the ‘IHS Fairplay database’ to establish EEDI baselines. Although the IMO introduced energy efficiency standards for ships over a decade ago, these regulations have not yet been applied to inland navigation. As a result, inland waterway vessels are exempted from the mandatory energy efficiency requirements. This regulatory gap limits the adoption of more energy-efficient designs that could reduce the environmental impact in inland shipping. Inland general cargo vessels play a significant role in the transportation of goods and optimizing their energy efficiency is crucial for minimizing emissions and improving sustainability. This paper presents an in-depth analysis of EEDI calculations based on IMO’s energy efficiency framework to suit inland cargo vessels, with vessel types representative of those operating in the Indian subcontinent. Additionally, the paper explores the effects of various fouling scenarios on energy efficiency and investigates how emissions can be reduced by employing various energy efficiency measures tailored to inland waterways. According to the Directorate General of Shipping (DG shipping), Government of India, the annual fuel consumption report for 2021 indicates that 69% of diesel/gas oil consumptions comes from ships of less than 5000 GT, that are operating on domestic routes. Moreover, these smaller vessels account for 18-19% of total carbon emissions from Indian ships. With projected increase in carbon emissions, it is crucial to prepare for emission indices applicable for inland water ways that allow the inland shipping towards a greener environment. The current study serves as a foundational step towards achieving sustainable goals in inland waterways. Given the significant impact of these emissions, it is essential to assess the data quality and operational parameters of the vessels operating in the inland waterways to ensure accurate EEDI calculations. Field studies reveal discrepancies between actual measurements and existing design data mainly in the principal particulars, main and auxiliary engine powers, and design speed. All this deviated ship information has a high influence on EEDI values. For this reason, ship data should be verified to find the correct ones, which is the key factor to establish EEDI baselines for inland going vessels. For the current study, data from 441 Indian general cargo vessels operating in inland waterways are considered, and the analysis of the data revealed instances of ambiguous or faulty information. Verified data from this analysis was then used to propose new EEDI baselines for inland cargo vessels. The proposed EEDI line represents CO2 emissions per tonne-mile and highlighting the necessity of precise operational data for effective calculation. Additionally, the validation of bio-fouling impacts on the EEDI is also conducted by referencing different fouling stages over various years.

Tornadoes can cause extensive destruction to the built environment, yet limited research in China has examined how building attributes and surrounding natural environments influence the vulnerability of rural buildings. Using the “6.23” tornado in Yancheng City, Jiangsu Province (China), this study applied Logistic Regression and eXtreme Gradient Boosting (XGBoost) models to analyze these relationships. A dataset of 2521 rural buildings shows that four building attributes, such as number of stories, structural type, usage, and floor area, were significantly associated with tornado damage to rural buildings at the 95% confidence level. The results suggest that taller buildings, larger areas, and stronger structures like brick-concrete and masonry are generally less vulnerable. Beyond building-level factors, geographic context and surrounding land use also played a critical role. To capture these broader effects, individual buildings were aggregated into 42 villages, and average village-level damage was calculated. Modeling at the village scale reveals that higher proportions of arable land (e.g., dry farmland), built-up land (e.g., rural settlements), and river surfaces tended to increase vulnerability, whereas transportation land had a mitigating influence. The consistency of results across Logistic Regression and XGBoost strengthens the reliability of these findings. Overall, this study highlights the combined importance of building design and environmental context in shaping rural building vulnerability to tornadoes. By providing data-driven evidence, the results support local governments in developing adaptation planning strategies for tornado-prone rural areas, particularly through informed decisions on building attributes and land use configurations to reduce future risks.

An event-based model and hybrid genetic search algorithm for an inland multi-size container transportation problem

The high frequency of traffic accidents in the land transportation sector, especially those involving intercity and interprovincial buses (AKAP), indicates that the safety aspect of passenger transportation is still a significant problem. This study aims to analyze the factors that contribute to the risk of accidents for AKAP bus drivers at the Jatijajar Type a Terminal, Depok. A quantitative approach is used with the Structural Equation Modeling (SEM) method to test the multidimensional relationship between driving behavior, drivers' mental and physical condition, company management, government regulations, environment and traffic, and vehicle factors to accident risk. The SEM-PLS analysis revealed that five factors significantly influenced the accident, collectively explaining 59.8% of the total variance in AKAP bus accidents. Mental and Physical Condition factors were the strongest predictors (coefficient = 0.302), followed by Risky Driving Behavior (0.273), Environment and Traffic (0.222), Company Management (-0.227), and Government Regulation (-0.194). Vehicle factors did not show a significant influence. Based on these findings, two priority strategies validated by experts were formulated: (1) Transformation of the driving profession through standardization of competencies and vocational education, and (2) Restructuring of wage and incentive systems to improve driver welfare and eliminate economic pressures that trigger risky behavior. This study provides a theoretical contribution by comprehensively modeling the factors of AKAP bus accidents and providing strategic recommendations that can be used as a reference for the government and bus operators in formulating more targeted policies to improve road transportation safety