The Yellow River Delta (YRD) stands as a globally significant wetland, playing a pivotal role in sustaining regional ecosystem stability and offering crucial ecosystem services to humanity. However, anthropogenic activities, particularly resource development, unavoidably disrupt the ecosystem, leading to the degradation of these vital services. Utilizing satellite remote sensing data, the InVEST model, and energy analysis, this study introduces the concept of ‘emergy’ as an ‘intermediate variable’ to investigate the spatiotemporal changes in the ecosystem service value of the YRD. Five distinct types of ecosystem services are selected for quantitative assessment and analysis of the YRD’s spatiotemporal evolution from 1990 to 2020. Results indicate a 63.7% decline in the total value of ecosystem services from 1990 to 2010, followed by a 16.5% increase from 2010 to 2020. The study also unveils spatial shifts in high- and low-value areas of ecosystem services and attributes these changes to rapid urbanization and alterations in land use and cover. The assessment of ecosystem service values concretizes the intangible ecosystem service functions of natural resources. This lays the foundation for establishing a mechanism that combines positive incentives and reverse pressure to achieve the economic valuation of ecosystem service.

Coastal urban areas play a pivotal role in regional economic growth, yet they are also sensitive regions where the natural environment interacts with human activities. Rapid urbanization has led to ecological issues, such as the degradation of key ecosystem services (ESs) in coastal cities. Understanding the impact of urbanization on the supply and demand of ESs in coastal cities is crucial for ensuring the healthy and sustainable development of the socio-economy in these areas. This study takes the coastal city of Qingdao as a case study, with a focus on the supply and demand relationships of seven key ESs—carbon sequestration, food production, habitat quality, recreational capacity, soil retention, water yield and marine aquaculture—as well as their responses to population growth, economic development, and spatial expansion, which are three distinct aspects of urbanization. The findings indicate that: (I) From 1992 to 2022, the evolution of different ESs exhibited variability, all displaying notable spatial imbalances. (II) During this period, the urbanization process in Qingdao had a pronounced negative effect on the supply and demand of ESs. Spatial urbanization had the most significant impact on carbon sequestration, food production, habitat quality, water yield, and marine aquaculture, while population urbanization most notably affected recreational capacity. (III) The sensitivity of different types of ESs to population, economic, and spatial urbanization varies. Carbon sequestration, food production, recreational capacity, soil retention, water yield, and marine aquaculture were most sensitive to economic urbanization, whereas habitat quality was most sensitive to spatial urbanization. This research provides a basis for decision-making in the sustainable development and comprehensive management of coastal cities and their ecosystems.

Accurately identifying ecological compensation areas and scientifically determining appropriate compensation amounts are crucial for establishing a robust ecological compensation mechanism, which in turn is key to promoting the coordinated development of ecological protection and high-quality economic growth. This study innovatively proposes a framework for ecological compensation termed “Accounting of Ecosystem Services Value–Identification of Priorities for Payers and Recipients–Calculation of Ecological Compensation Amount (ESV–PPR–ECA)”. It utilizes the InVEST model and the emergy method to assess the value of ecosystem services, constructs the Ecosystem Payment and Recipient Priority Sequence (EPRPS) Model to identify the payers, recipients, and their priorities for ecological compensation, and employs the conversion factor method to calculate the Ecological Compensation Amount (ECA). This framework aims to address the questions of “How should compensation be provided?”, “Who should compensate whom?”, and “How much compensation is necessary?”, ensuring the optimal use of ecological compensation funds and providing a scientific basis for inter-regional ecological compensation. The study’s findings indicate that the total Ecological Compensation Amount for the Yellow River Delta in 2020 was 3.848 billion RMB, with the total amount receivable being 4.032 billion RMB and the total amount payable being 184 million RMB. The compensation funds should be prioritized for tideland and the Yellow River, and venture, cropland and industrial land should be the first to contribute compensation. Additionally, the Ecosystem Service Value of the Yellow River Delta showed a declining trend from 2015 to 2020, underscoring the urgent need to establish a horizontal compensation mechanism for the region. Such a mechanism would incentivize environmental protection and the construction of ecological civilization, ultimately enhancing ecosystem service functions. Therefore, we recommend the implementation of horizontal fiscal transfers, where financial assistance is provided from paying areas to recipient areas, offering a scientific reference for the establishment of a horizontal compensation mechanism within the Yellow River Delta.

Artillery, as the primary firepower weapon for ground and naval forces, plays a crucial role in modern warfare. However, modern information warfare poses severe challenges to artillery systems. An efficient and accurate artillery firing data resolution algorithm is a crucial component in enabling modern combat capabilities for artillery. In response to these challenges, this paper proposes an improved genetic algorithm (GA-LFPSO) for solving artillery firing data. The proposed algorithm addresses and improves upon issues such as population initialization, local optimum problems, and calculation efficiency. The initialization of the algorithm’s population incorporates initial solutions based on Levy flight to enhance population diversity. Additionally, the genetic algorithm integrates the particle swarm optimization algorithm by guiding the population’s iterative selection with optimal solutions generated during its iterations, further enhancing the convergence speed of the algorithm. In the final phase of the algorithm, new individuals are generated using Levy flight based on a portion of the existing individuals and integrated into the population, thereby improving the algorithm’s global search capability. To validate the algorithm, simulations were conducted using a ballistic model and compared with four other algorithms. The results demonstrate that the proposed GA-LFPSO algorithm exhibits rapid convergence, robust search capabilities, and exceptional performance in solving the firing data.

Understanding ecosystem service characteristics along urban-rural gradients is vital for enhancing the well-being of urban and rural residents. Despite this importance, prior research has neglected the dynamic evolution of urban-rural gradients during urbanization. This study investigates the spatiotemporal variations of four ecosystem services—habitat quality, carbon sequestration, water yield, and soil retention—along the urban-rural gradient in Jinghong City, China. We propose a method for identifying the gradient using the inverse S function of urban land density distribution and concentric analysis. From 2000 to 2020, ecosystem service supply capacity in Jinghong City continuously declined, indicating degradation over the two decades. The urban-rural gradient zone is classified as core area, inner urban area, suburban area, and urban periphery, each experiencing outward expansion, reflecting significant urbanization. Changes in ecosystem services along the gradient revealed consistently high losses in habitat quality, carbon sequestration, and overall services in the inner urban area, while water yield and soil retention suffered the greatest losses in the urban periphery. As urbanization expanded outward, the loss of these services shifted from the inner urban area to the suburban and urban periphery. These results support decision-making in urban planning and sustainable development for urban-rural regions.

Coastal cities, as centers of economic and industrial activity, accommodate over 40% of the national population and generate more than 70% of the GDP. They are critical centers of carbon emissions, making the accurate and long-term analysis of spatiotemporal carbon emission patterns crucial for developing effective regional carbon reduction strategies. However, there is a scarcity of studies on continuous long-term carbon emissions in coastal cities. This study focuses on Qingdao and explores its carbon emission characteristics at the city, county, and grid scales. Data from multi-source are employed, integrating net primary production (NPP), energy consumption, and nighttime light data to construct a carbon emission estimation model. Additionally, the Tapio model is applied to examine the decoupling of GDP from carbon emissions. The results indicate that the R² of the carbon emission inversion model is 0.948. The central urban areas of Qingdao’s coastal region are identified as hotspots for carbon emissions, exhibiting significantly higher emissions compared to inland areas. There is a notable dependence of economic development on carbon emissions, and the disparities in economic development between coastal and inland areas have resulted in significant geographical differentiation in the decoupling state. Furthermore, optimizing and transitioning the energy structure has primarily contributed to carbon reduction, while exceptional circumstances, such as the COVID-19 pandemic, have led to passive fluctuations in emissions. This study provides a scientific reference for coastal cities to formulate targeted carbon reduction policies.