In order to improve the efficiency of air transportation, reduce transportation costs and carbon emissions, the evolutionary game method was adopted to explore the influencing factors of the cargo alliance between the government and airlines. The system dynamics model (SD) was used to conduct simulation experiments on the game evolution process. The results indicate that the strategic choices between airlines are influenced by investment costs and alliance benefits, while the government’s strategic choices are influenced by factors such as the carbon emission penalty coefficient paid by airlines, carbon tax subsidy amounts, social benefits, and regulatory costs. In the long run, the government should establish a dynamic subsidy mechanism and increase the diversity of subsidies to enhance the innovation and core competitiveness of airlines.

In order to study the molecular weight and molecular structure changes of asphalt under ultraviolet aging and the mechanism of their effects on macro properties, gel permeation chromatography and nuclear magnetic resonance tests were carried out on four commonly used asphalt, respectively. The molecular weight composition changes, such as molecular weight and molecular relative mass distribution, and the molecular structure composition changes, such as hydrogen spectrum, carbon spectrum, hydrogen atom content and molecular structure parameters were studied. On the basis of macroscopic rheological tests, the molecular composition of asphalt rheological properties was characterized by correlation analysis, and the molecular mechanism of ultraviolet aging macroscopic properties was analyzed. The results show that ultraviolet aging causes the agglomeration of molecules in asphalt, small molecules decreases and aggregates into large molecules, and the molecular weight distribution boundary narrows gradually. From the changes of hydrogen atoms and molecular structure parameters, it can be seen that the alkyl substituents on the aromatic ring in the asphalt increase after ultraviolet aging, resulting in the increase of the volume and stability of the aromatic ring, and the increase of molecular backbone stiffness. On the macro level, the elastic properties of asphalt increase. The phase angle, rutting factor, irrecoverable compliance and recovery rate of asphalt before and after ultraviolet aging were obtained by macroscopic rheological tests. The correlation analysis shows that the rheological properties are most affected by condensation degree parameters, substitution rate of peripheral hydrogen, average molecular weight and branched degree of alkyl chain.

The displacement response of a bridge is identified as a fundamental condition for the structural health monitoring and safety assessment of bridge structures. In order to fully leverage the advantages of machine vision for measuring structural displacements and to enhance its applicability, a structural displacement monitoring method based on the pinhole camera model was proposed. Sparse optical flow was employed to track structural feature points, achieving sub-pixel level image displacements. By employing the optical geometric relationships of camera imaging, an analytical solution was established between real-world displacements and image displacements. The image displacements were then substituted into algebraic relationships to obtain the true structural displacements. In the indoor experiments on dynamic load displacement identification of a simply supported bridge model, compared to the measurements obtained using a linear variable differential transformer displacement meter, the proposed method achieves a maximum error within 6% for pitch angles up to 30° and yaw angles up to 35°, thereby meeting the application requirements for monitoring the displacement deformations of bridge structures.

Shared bikes represent a crucial component of urban transportation. The randomness of user demand for shared bikes with fixed piles leads to unbalanced demand in time and space, and even the difficulty in renting a bike, which cannot meet the user demand during peak hours. Therefore, high-frequency users frequently travel to nearby stations to rent a bike for serving, which means that there are implicit demands. As for the hidden demand, firstly, the state changes of the site were described by the rental number and the return number, and the critical state of the reference site was determined by mining the user travel conditions of nearby sites. The hidden demand of the site was determined based on the site state change diagram and the demand judgment model. Then, according to the real needs of the site, the long short-term memory(LSTM) network prediction model was established, and the regional scheduling model of shared bicycles based on the real needs was established. The model takes the cost minimization as the goal, and obtains the path with minimum scheduling cost through genetic algorithm, which provides a reference for balanced scheduling based on real demand. The results demonstrate that, when transportation costs are similar, the scheduling method under real demand can alleviate the problem of users’ difficulty in renting a bike, thereby reducing the loss of high-frequency users.

Aiming at the problem of short effective prediction time for the movement history of amphibious aircraft in waves, the statistical values of amphibious aircraft movement over a period of time were proposed to predict, and a prediction model for the statistical characteristics of amphibious aircraft movement was constructed based on long short-term memory neural networks(LSTM). Taking the NACA TN 2929 amphibious aircraft as an example, based on its numerical simulation data, the statistical values of the three degrees of freedom motion of heave, roll, and pitch of amphibious aircraft under sea conditions of level 3, 4, and 5 were predicted, and their prediction effects were analyzed in detail. The results show that the LSTM neural network-based model for predicting the statistical characteristics of amphibious aircraft motion has good prediction accuracy. In practical engineering applications, this model can accurately predict the statistical values of amphibious aircraft motion in the future, providing auxiliary decision-making information for offshore operations.

With the increasingly serious problem of climate change, green and low-carbon operations have become an important principle for the sustainable development of the air transportation industry. Taking a single runway transport airport as the research object and green and low-carbon and passenger walking distance as the optimization objective, a green and low-carbon gate assignment model under multiple scenarios was constructed, and a genetic-tabu search combined optimization algorithm was designed to solve it. Finally, a transport airport in northeast China was taken as an example for simulation experiment. The experimental results are shown as follows. In the optimal assignment scheme, if considering green and low-carbon, the fuel consumption can be reduced by 3.1%, the taxiing distance of the aircraft by 3.1%, HC emission by 4.2%, CO emission by 3.6%, NO_X emission by 3.1%, and CO₂ emission by 3.1% comparatively. But passenger walking distance can be increased by 5.3% at the same time. If considering green and low-carbon as well as the interests of the passengers, the fuel consumption can be decreased by 2.1%, the taxiing distance of the aircraft by 2.2%, HC emission by 3.8%, CO emission by 2.7%, NO_X emission by 2.0%, CO₂ emission by 2.1%, and passenger walking distance by 2.1% comparatively. Thus, it is possible to strike a balance between green and low-carbon development and the interests of travelers.

The quantitative monitoring and evaluation of the terrestrial ecological environment status helps to understand the changes in ecosystems and their driving factors, and is of great significance for the government to guide regional ecological environment management, achieve ecological protection and socio-economic coordinated development. Based on long-term multi-source satellite remote sensing data, a land ecological environment status index (LESI) evaluation model was constructed by coupling five indicators including greenness, heat, humidity, dryness, and air pollution using covariance principal component analysis. Four strategies, including Augmented Dickey Fuller (ADF) test, Biplot biplot, correlation analysis, and cross validation, were used to demonstrate the good stationarity, rationality, comprehensive representativeness, and regional adaptability of the model. On this basis, the spatio-temporal characteristics and evolution patterns of the land eco-environment status (LES) in the the Taihu Lake Basin from 2001 to 2021 were assessed, the driving factors of LES changes were discussed, and the contributions of climate change and human activities were quantified. The results show that the eco-environment quality of the the Taihu Lake Basin is declining first and then stable. The average annual LESI decreases significantly from 0.639 in 2001 to 0.523 in 2009 (-18.2%), and then tends to be stable. The spatial-temporal variation of LESI in Taihu Lake Basin is obviously different. The area where the ecological environment quality remains stable or improved (68.8%) is significantly larger than the area where the ecological environment quality is declining (31.2%), of which Hangzhou and Huzhou have the best eco-environment quality and remain stable. Shanghai and Suzhou are relatively poor and have significant fluctuations. The contributions of temperature, precipitation and night light to LESI are 0.03, 0.19 and 0.78, respectively, indicating that the eco-environment changes in the the Taihu Lake basin in recent 21 years are mainly dominated by human activities, while only some forest mountain areas and wetland areas are affected by climate change. The LESI model established in the study can effectively monitor and quantitatively evaluate changes in the eco-environment, providing scientific support for the government to formulate ecological environment protection policies and promote high-quality development.

The problem of mine water pollution from abandoned mines after integration is becoming increasingly serious with the integration of coal resources and the merger and reorganisation of coal companies. An accurate understanding of the development mechanism of mine water quality in abandoned coal mines is an important prerequisite for the protection and use of mine water and the effective prevention and control of groundwater pollution. The leaching behaviour of Fe³⁺ and Mn²⁺ and the changes of related water quality indices were investigated by the long-term indoor water-coal immersion test based on the project practice of Shendong mining area. The results show that the solubility of Fe³⁺ is “wave-like”, and the solubility of both samples reaches the lowest value at the 84th day after immersion, while the solubility of Mn²⁺ remains relatively stable after a rapid reaction (the first day). The causes of solubility variations were further analysed by ion ratio coefficient method and Pearson correlation coefficient method, and it was found that mine water in goaf may be affected by mining activities, and the water quality of mine water is strongly influenced by the dissolution of silicate rocks and gypsum. The main water-rock interactions in mine water in the goaf area include the dissolution of silicate rocks and evaporative rocks and the alternating adsorption of cations. For the rational development and utilisation of mine water in China, it is of great importance to study the characteristic pollutant ion change law of mine water in the goaf area.