Transmission Path Research Articles

Magnetic carbon composites derived from biomass with excellent microwave absorption capacity

It is well known that magnetic iron oxide (Fe3O4) and carbon-based materials are good microwave absorbing materials. However, the frequency bands in which Fe3O4 absorbs electromagnetic waves are usually concentrated in the low-frequency region, whereas carbon materials are in the high-frequency region. Therefore, this study aims to deal with the limitation of the absorption bands of these two substances. In this work, this Fe3O4/C composite with high performance microwave absorption was successfully adoption of hydrothermal-calcination process using mangosteen shells as a biomass carbon material, and with a thickness of 1.97 mm, the optimal reflection loss of the sample can reach −67.49 dB, and the frequency band that can be absorbed is 4.32 GHz. The interface polarization, dipolar polarization and eddy current loss in Fe3O4 and carbon materials produce synergistic effects, and the porous conductive network increases the electromagnetic wave transmission path and generates conductive losses, which results in composites with excellent electromagnetic wave absorption properties. The findings indicated that a composite compound of Fe3O4 and carbon-based material was successfully synthesized by hydrothermal method and obtained a materials with outstanding electromagnetic wave absorption properties and high absorption bandwidth.

Privacy-Preserving Computing Services for Encrypted Personal Data Through Streams Over Distributed Ledgers

The growing adoption of wearables is driving the demand for personalized services that leverage unprocessed data, such as biometric and health information, to enhance user experiences and support through software applications. However, several existing use cases involving this information still prioritize traditional schemes, neglecting user privacy. Consequently, the transparency of data transmission paths and the potential for tampering remain ambiguous when users share data with service providers. In this paper, we propose the application of an Internet of Things device-focused distributed ledger as an underlying layer for the transmission of encrypted data using streams. Moreover, our proposal enables data recording for future events and the implementation of multi-subscriber models, allowing client information to be shared securely with different service providers. Through simulation experiments conducted on constrained devices, we demonstrate that our proposed framework efficiently transmits large ciphertexts through streams on a distributed ledger, overcoming the inherent limitations of such networks when dealing with substantial data volumes. Ultimately, the performance metrics presented prove that the proposed model is suitable for real-world applications requiring continuous data collection by wearables and subsequent transmission to service providers.

Investigation of signal coupling circuit for NbN-based SIS mixer operated at 650 GHz

Superconductor-insulator-superconductor (SIS) mixers are the most sensitive coherent detectors in the terahertz region and are extensively utilized in astronomical research and atmospheric observation. In order to improve the detection accuracy of frequency, reduce the loss of signal in the transmission path, and reduce noise temperature, it is important to design a signal coupling circuit with high coupling efficiency. In this paper, with the help of a high-frequency structure simulator, a signal coupling circuit was designed based on a waveguide NbN-based SIS mixer at 650 GHz. The return loss and embedding impedance of this SIS mixer were investigated from 600 to 720 GHz. The effects of the SIS mixer chip’s bow-tie probe angle, substrate thickness, and chip slot height were calculated and analyzed. The results show that the return loss is lower than -16 dB in the 600 to 720 GHz band, and the embedding impedance is around 60 Ω, which can provide a good reference for the development of waveguide SIS mixers.

Z-scheme heterojunction of TiO2/NH2-MIL-125(Ti) growing on carbon fibers cloth: Photocatalytic degradation of tetracycline and toxicity analysis

Photocatalysis stands out as a promising and eco-friendly method for antibiotics removal, yet traditional photocatalysts, mainly in powder form, are often prone to detachment and loss, making them difficult to recycle and reuse. In this work, we address this challenge by using carbon fiber (CF) cloth with a large area as a carrier for catalysts. To improve the photocatalytic efficiency, we synthesized TiO2 nanorods on the surfaces of CF cloth and incorporate NH2-MIL-125 (Ti) on them, thus the Z-scheme heterojunctions CF/TiO2/NH2-MIL-125(Ti) was obtained. In order to fully understand the structural properties and performance advantages of CF/TiO2/NH₂-MIL-125 (Ti) composites, scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), X-ray photoelectron spectroscopy (XPS), UV–visible diffuse reflectance spectroscopy (DRS), photoluminescence spectroscopy (PL), Brunauer-Emmett-Teller (BET), Mott-Schottky (M-S) and valence band X-ray photoelectron spectroscopy (VB-XPS). Due to the special electronic transmission path of the Z-scheme heterojunctions, the CF/TiO2/NH2-MIL-125(Ti) composite achieve 95.30 % degradation of tetracycline (TC) within 210 min. The composite also shows exceptional reusability, with a degradation rate of 93.55 % maintained even after four cycles. Finally, we proposed a pathway and catalytic process for the decomposition of TC by CF/TiO2/NH2-MIL-125(Ti) and performed toxicity assessments of TC and its precursors using T.E.S.T. software. This novel photocatalyst composite offers a green and efficient approach for treating antibiotic wastewater, presenting a significant advancement in environmental remediation strategies.

Climate transition risk and enterprise default probability

AbstractPreventing and controlling the risk of enterprise default is an important way to maintain financial stability. When mitigating and adapting to climate change, it is important to study whether climate transition risk affects the probability of enterprise default. This article systematically analyzes data for Chinese‐listed companies from 2000 to 2019 and finds that climate transition risk significantly increases enterprise default probability (EDF). In addition, pilot carbon emission trading schemes and national carbon emission trading increase this effect. Financing constraints and profitability act as transmission channels; the transmission path, in turn, is influenced by the enterprise environment, social, and governance (ESG) factors and executive compensation. Excellent enterprise ESG performance can lower the positive impact of climate transition risk on EDF. However, higher executive compensation has the opposite effect: high compensation is associated with higher risk. When considering different business types, climate transition risk is more likely to increase the default probability of small assets or non‐state‐owned enterprises. This study helps describe the internal relationship between climate transition risk and EDF, and provides insights to better prevent and address the problem of enterprise debt default caused by climate transition risk.

The effect of interpersonal relationships on epidemic spreading in weighted multilayer networks

During the epidemic outbreak, people's reactions to social contacts of varying degrees of intimacy exhibited significant differences. Historical data further reveal that interactions between groups play a crucial role in the epidemic's transmission chain. In light of this, it is essential for epidemiological models to account for more complex interaction mechanisms. Based on this understanding, we have developed a weighted dual-layer network model. One layer simulates the spread of information through 2-simplexes, while the other simulates the actual transmission paths of the disease based on physical contact. The weight between two nodes represents individual differences in information acceptance and self-protection among neighbors with different relationships. We conducted a theoretical analysis using the Micro-Markov Chain Approach to examine transmission behaviors, and we also implemented numerical simulations using the Monte Carlo Method. The simulation results aligned with the theoretical analysis, indicating that stronger interpersonal relationships can enhance information dissemination, prompting more individuals to adopt protective measures, which in turn helps curb the spread of the disease.

Robust AI Based Bio Inspired Protocol using GANs for Secure and Efficient Data Transmission in IoT to Minimize Data Loss

Objectives: To propose an AI-based protocol to enhance the reliability and security of IoT data transmission in a robust manner. Deep learning with bio-inspired methods is employed to address real-time challenges such as route optimization, data integrity, error recovery, and end-to-end delay in order to minimize data loss and maximize the transmission rate. Methods: Generative Adversarial Networks (GANs) are used to enhance the robustness of the protocol in combination with a bio-inspired Artificial Immune System (AIS) to detect IoT network anomalies and responds to malicious activities by using the adaptive learning capabilities of IS. Hybrid Automatic Repeat Request (HARQ), an error recovery method, is utilized to detect network errors in order to correct and retransmit data to the destination during error-prone network conditions. Queue learning action sets are used to discover the finest path for efficient data transmission. The OMNeT++ simulator is used to assess the performance of the proposed BIP-GANs protocol. The performance results are compared with the prevailing data transmission protocols, such as EAP-IFBA, DNN-CSO, and ALO-DHT. Findings: The suggested BIP-GANs data transmission protocol outperforms with promising results, with an energy consumption rate of 6%, 8 seconds data transmission speed, 6 second less delay rate, 98% robustness (security and confidentiality), 98.5% alive nodes, and 99% network life span, which is higher than the prevailing methods. Novelty: This research study provides a comprehensive solution to secure and efficient data transmission by integrating the AI-based bio-inspired BIP-GANs method to address the security and data transmission challenges of existing methods such as EAP-IFBA, DNN-CSO, and ALO-DHT in terms of energy consumption rate, transmission speed, delay rate, life span of the network, robustness, and number of alive nodes. Keywords: Artificial Intelligence, Generative Adversarial Networks, Error Recovery, Secured Data Transmission, Deep Learning, Bio­Inspired Algorithm

Energy-Efficient Algorithm for Data Path Selection in High-Density Wireless Sensor Networks

Relevance. Increasing the number of sensor devices per unit area consequently reduces the physical distance between the devices in the sensor network. Such networks are usually deployed over a large area and the sensor device that wants to transmit a data packet is located far away from the base station. In such a case, the source device is challenged to choose a transmission path that consumes the least amount of energy resources and satisfies the delivery time requirements. The objective of this study is to develop and validate the effectiveness of an empirical algorithm for selecting a transmission path that reduces the energy consumption of high-density wireless sensor networks. Methods of system analysis, analytical modeling, geometry and probability theories are used. Solution. It is assumed that the sensor network is deployed in a limited area and is a set of devices that are connected to each other informationally and energetically. When building data transmission routes, any sensor devices can be used as repeaters. At the same time, the increase in the number of repeaters leads to an increase in the time of data delivery. Novelty. It is assumed that the sensor network is deployed in a limited area and is a set of devices that are connected to each other informationally and energetically. Any sensor devices may be used as repeaters when constructing data transmission routes.Significance (theoretical). Dependences of power consumption level on various system parameters affecting the processes of functioning of high-density wireless sensor networks have been obtained. Significance (practical). The proposed empirical algorithm for selecting a rational data transmission route in a wireless sensor network allows us to determine, among all alternatives, the route to the coordinator that requires the least power. The effectiveness of the proposed empirical power-saving algorithm is confirmed by simulation modeling.

Susceptibility of Synanthropic Rodents (Mus musculus, Rattus norvegicus and Rattus rattus) to H5N1 Subtype High Pathogenicity Avian Influenza Viruses.

Synanthropic wild rodents associated with agricultural operations may represent a risk path for transmission of high pathogenicity avian influenza viruses (HPAIVs) from wild birds to poultry birds. However, their susceptibility to HPAIVs remains unclear. In the present study, house mice (Mus musculus), brown rats (Rattus norvegicus), and black rats (Rattus rattus) were experimentally exposed to H5N1 subtype HPAIVs to evaluate their vulnerability to infection. After intranasal inoculation with HA clade 2.2 and 2.3.2.1 H5N1 subtype HPAIVs, wild rodents did not show any clinical signs and survived for 10- and 12-day observation periods. Viruses were isolated from oral swabs for several days after inoculation, while little or no virus was detected in their feces or rectal swabs. In euthanized animals at 3 days post-inoculation, HPAIVs were primarily detected in respiratory tract tissues such as the nasal turbinates, trachea, and lungs. Serum HI antibodies were detected in HA clade 2.2 HPAIV-inoculated rodents. These results strongly suggest that synanthropic wild rodents are susceptible to infection of avian-origin H5N1 subtype HPAIVs and contribute to the virus ecosystem as replication-competent hosts. Detection of infectious viruses in oral swabs indicates that wild rodents exposed to HPAIVs could contaminate food, water, and the environment in poultry houses and play roles in the introduction and spread of HPAIVs in farms.

Effectiveness of probabilistic contact tracing in epidemic containment: The role of superspreaders and transmission path reconstruction.

The recent COVID-19 pandemic underscores the significance of early stage nonpharmacological intervention strategies. The widespread use of masks and the systematic implementation of contact tracing strategies provide a potentially equally effective and socially less impactful alternative to more conventional approaches, such as large-scale mobility restrictions. However, manual contact tracing faces strong limitations in accessing the network of contacts, and the scalability of currently implemented protocols for smartphone-based digital contact tracing becomes impractical during the rapid expansion phases of the outbreaks, due to the surge in exposure notifications and associated tests. A substantial improvement in digital contact tracing can be obtained through the integration of probabilistic techniques for risk assessment that can more effectively guide the allocation of diagnostic tests. In this study, we first quantitatively analyze the diagnostic and social costs associated with these containment measures based on contact tracing, employing three state-of-the-art models of SARS-CoV-2 spreading. Our results suggest that probabilistic techniques allow for more effective mitigation at a lower cost. Secondly, our findings reveal a remarkable efficacy of probabilistic contact-tracing techniques in performing backward and multistep tracing and capturing superspreading events.

The role of green finance in the construction of new energy system: Evidence from China

Under the rapid development of energy transition and new energy technologies, it is of practical significance to construct a new energy system and explore the empowerment mechanism of green finance on the new energy system. This study conducted empirical research, analyzing the specific theoretical mechanism and transmission path of green finance in constructing a new energy system. The research results indicate that green finance directly promotes the construction of a new energy system, further driving the improvement of technical innovation levels, and facilitating the establishment of more environmental protection institutions, thereby indirectly promoting the construction of a new energy system. Additionally, green finance has a stronger promotion effect under conditions of lower openness levels, economic development levels, urbanization rates, and proportions of the tertiary industry. Moreover, under higher government fiscal expenditure conditions, green finance also generates a greater promotion effect. As the development level of the new energy system increases, the marginal impact of green finance first rises, then stabilizes, and ultimately decreases. Within the empirical analysis framework, this paper provides a novel perspective on the empowerment of green finance, contributing to the construction of a new energy system under new development conditions.

A holistic approach to different regulations for acoustic improvements in industrial facilities

With the developing technology and mechanization, the number of industrial facilities has increased. It is important for the worker’s physical and mental health to be in suitable working conditions. This paper analyses the regulations applied in the examination and evaluation of the acoustic environment in industrial facilities. The European Parliament and Council Directive, the United States, Singapore, Canada, Australia, Mexico, Japan, and WHO principles were analysed in detail. Simultaneously, analyses were conducted on the auditory perception of the workers in industrial facilities. As a result of the study, 85, 87, and 90 dBA noise exposure levels were determined for 8 h in different regulations examined. It has been determined that the regulative systems for the auditory perception of the workers in industrial facilities are insufficient. It was found necessary to develop regulation systems for evaluating noise exposure levels and the auditory perception of the workers together. It is important for the occupational health and safety of workers to develop a holistic approach in the update and revision of international regulation and to evaluate the control mechanisms within this scope. The protection of mental and physical health of the workers is presented as the most fundamental requirement. Moreover, it should be ensured that the noise control measures that can be taken (at the source, at the transmission path, and at the receiver) are formed by reducing the noise exposure and increasing the auditory perception of the workers in a positive view.

Multifunctional organic-inorganic hybrid coating for enhanced bronze corrosion protection

Bronze relics with vital historical, artistic, and scientific value, are one of the significant symbolizations of human civilization. However, due to the long burial time and the change in storage conditions, an inevitable and thorny problem arises in preventing the ancient bronze relics from corrosion. Coatings have great potential for metal corrosion protection at present. This study prepared a multifunctional coating consisting of zinc oxide (ZnO), titanium dioxide (TiO2), and fluoroethylene vinyl ether (FEVE) polymer by an organic-inorganic hybrid, which was applied onto the surface of corroded bronze using a self-assembly method and spraying. The rough structure of composite coating resembling that of the mastoid structure found on lotus leaf, effectively prolongs the transmission path of corrosive ions while preventing bronze contact with the corrosive media. Additionally, this study mainly investigated the bronze anti-corrosion mechanism through an electrochemical analysis perspective. Electrochemical tests revealed the lower corrosion current density, and the positive corrosion potential of multifunctional FEVE@ZnO/TiO2 coating immersion in 3.5 wt% NaCl solution. The experimental results demonstrate that the synergistic effect of organic-inorganic significantly enhances corrosion resistance by retarding the corrosion process and providing active protection against corrosion. The multifunctional coating also exhibits exceptional self-cleaning properties and weatherability when without changing the bronze color and appearance. Consequently, this preparation strategy and research approach for constructing a multifunction coating has a great application prospect in the conservation of bronze relics and metal anti-corrosion.

Direct Z-scheme GeC/GaSe heterojunction by first-principles study for photocatalytic water splitting

In this study, we constructed the direct Z-scheme heterojunction by vertically stacking monolayers of GeC and GaSe. And systematically explored its stability, electronic structure, optical absorption characteristics and photocatalytic mechanism with first principles calculations. Our results show that the GeC/GaSe heterojunction possesses an indirect-gap of 1.88 eV and exhibits a staggered energy-band structure. In comparison to the individual monolayers of GeC and GaSe, the GeC/GaSe heterojunction has more excellent absorption of far-ultraviolet and visible light. And the electrons and holes in the GeC/GaSe heterojunction have a transmission path resembling the letter Z. There is also an internal electric field from GeC to GaSe in the heterojunction, which accelerates the photoelectrons and holes along the Z direction when the heterojunction receives light. Furthermore, further studies suggest that the GeC/GaSe heterojunction can be utilized as a photocatalytic material for water splitting under pH = 0–14. Besides, the bandwidth and optical absorption properties of the GeC/GaSe heterojunction can be adjusted by biaxial strains. Moreover, Gibbs free energy calculations during water splitting demonstrate that the GeC/GaSe heterojunction exhibits a highly driven force for both OER and HER. Thus, direct Z-scheme GeC/GaSe heterojunction has the capability to be a promising photocatalyst for water splitting.

Kirkendall Effect-Induced Ternary Heterointerfaces Engineering for High Polarization Loss MOF-LDH-MXene Absorbers.

Heterogeneous interfacial engineering has garnered widespread attention for optimizing polarization loss and enhancing the performance of electromagnetic wave absorption. A novel Kirkendall effect-assisted electrostatic self-assembly method is employed to construct a metal-organic framework (MOF, MIL-88A) decorated with Ni-Fe layered double hydroxide (LDH), forming a multilayer nano-cage coated with Ti3C2Tx. By modulating the surface adsorption of Ti3C2Tx on LDH, the heterointerfaces in MOF-LDH-MXene ternary composites exhibit excellent interfacial polarization loss. Additionally, the Ni-Fe LDH@Ti3C2Tx nano-cage exhibits a large specific surface area, abundant defects, and a large number of heterojunction structures, resulting in excellent electromagnetic wave absorption performance. The MIL-88A@Ni-Fe LDH@Ti3C2Tx-1.0 nano-cage achieves a reflection loss value of -46.7 dB at a thickness of 1.4mm and an effective absorption bandwidth of 5.12 GHz at a thickness of 1.8mm. The heterojunction interface composed of Ni-Fe LDH and Ti3C2Tx helps to enhance polarization loss. Additionally, Ti3C2Tx forms a conductive network on the surface, while the cavity between the MIL-88A core and the Ni-Fe LDH shell facilitates multiple attenuations by increasing the transmission path of internal incident waves. This work may reveal a new structural design of multi-component composites by heterointerfaces engineering for electromagnetic wave absorption.

An inter-satellite laser occultation method profiling atmospheric temperature and pressure from troposphere to lower mesosphere

We propose a laser occultation method for simultaneous profiling atmospheric temperature and pressure. Measurements can be performed on the optical link between two low-orbit satellites, where frequency-stepwise laser pulses are transmitted from one to the other. These pulses, covering several oxygen absorption lines in the wavelength domain, measure the broadened atmospheric absorption optical depth along the transmission path with a spectral resolution of tens of megahertz. In this way, atmospheric temperature and pressure are obtained by analysing the retrieved shape and intensity of the spectral lines. With the motion of the two satellites, the inter-satellite optical link penetrates different atmospheric layers at various altitudes, enabling the measurement of the vertical structure of atmospheric thermodynamic parameters from the troposphere to the lower thermosphere. This paper presents an end-to-end simulation of the proposed method, including models for laser occultation beam tracing, radiative transfer, and data inversion. The simulation results reveal that with minimal satellite payload resources, this method can accurately measure temperature and pressure at a vertical resolution of 100 m from 5 km to 90 km altitude with accuracies of ±1.5 K and 5 %, respectively. As the proposed differential absorption laser occultation method is independent of the hydrostatic equilibrium hypothesis for data inversion, it can eliminate errors associated with prior data at reference altitudes. It is believed that our method has provided a promising approach to laser satellite constellation for atmospheric observation.

A dynamic analysis of UAV -based IoT networks for efficient communication using falcon optimization approach

Unmanned Aerial Vehicles (UAVs) play a pivotal role in Internet of Things (IoT) applications by sensing data, conducting continuous surveillance, and maintaining connectivity among users. However, their high mobility and continuous surveillance for data transmission result in high energy consumption, possibly resulting in lesser network performance, including link failure, node depletion, data loss, and high delays. To address these challenges, a novel scheme termed as 'On-Demand Cross-Layered Falcon Optimization Approach (OCLFO)' has been proposed to enhance connectivity and optimize network performance in UAV-based IoT systems. The on- demand Cross-Layer Optimization (CLO) scheme facilitates data transmission across each layer of the OSI model. CLO is applied to the design of UAVs with the integration of on-demand, based on the queuing size. Falcon Optimization Approach (FOA) has been integrated with the CLO to overcome the energy consumption drawback, and provide successful data transmission between UAV users with the help of fitness value. The fitness value depends maximum on the energy and minimum on the queuing size, and this provides the energy efficient routing path for an efficient data transmission. The proposed OCLFO aims to optimize energy consumption while ensuring successful and expedited data transmission among UAV users. Simulations have been conducted using a network simulator to analyse Quality of Service (QoS) parameters, considering high mobility scenarios by varying energy levels such as 100 J and 200 J. Compared to the existing optimization algorithms, the proposed OCLFO achieves high delivery ratio, high throughput, less delay, lesser energy consumption and enhanced link efficiency.

Adjustable stereo path design method based on pin-sculpture acoustic topological insulator with Z-dislocation defect immunity

The field of topological protected wave engineering, inspired by quantum mechanics, has generated significant interest. Acoustic analogs of electronic topological insulators provide new opportunities for manipulating sound propagation with unconventional acoustic edge modes that are immune to backscattering. Numerous reports have been published on the design of two-dimensional acoustic topological insulators (ATIs). However, the sound path of a two-dimensional design is simple, and its ability to control sound waves is limited. On the other hand, the design of 3D ATIs is relatively complex, making it difficult to manufacture and limiting its versatility. Based on the design idea of the 2D ATIs, inspired by the art named 3D pin-sculpture, an adjustable structure of a finite size consisting of spindle-shaped units with a variable cross section is designed to realize flexible path transformation. Furthermore, unlike two-dimensional structural defects, such as cavities and disorder, the analysis of vertical dislocation defects in finite-sized structures allows for the design of local sound propagation along the z-direction, providing a concept for constructing a stereo path. The designed structure also serves two functions: acoustic switch and delay. This idea offers an alternative approach to designing complex sound transmission paths.

A complex network-based transmission mechanism and target control method for reducing carbon emission

To achieve carbon neutrality for China, the transmission mechanism, path, diffusion effect,and allocation of Emission Reduction Targets (ERT) among industries must be investigated. Setting short-term ERT will create a reverse pressure mechanism for the industry's carbon reduction, ensuring the achievement of carbon emission control target. However, few studies have explored how to influence the entire system by controlling key industries from the perspective of network control. Therefore, this study investigates Inter-industry Carbon Emission Transfer (ICET) in China from 1997 to 2017,and found that ICET can achieve fair distribution of ERT. Inspired by the controllability theory of complex networks to integrate the driving factors, the transmission paths, diffusion effects, and allocation of ERT into a unified analytical framework. Then, breaking the traditional top-down hierarchical decomposition mechanism and transforming it into a bottom-up target forcing mechanism, a decomposition algorithm for the total control target was proposed.The results reveal that ICET accounts for the majority of carbon emission. The characteristics of network structure have a significant impact on the ICET.Different industries have varying control capabilities. Compared with industry-wide control, target control on the Minimum Control Industry Set (MCMCS) has a slightly worse emission reduction effect, but the economic loss is smaller, making it an effective policy choice.

Mapping the inter-provincial pathways of resources and socio-economic impacts in China's just transition of coal power

In the sustainable transition of the power system, China's resource distribution characteristics lead to a distinct geographical separation between the main production and consumption areas of coal and coal power. This separation leads to the transmission of complex inter-regional social risks and responsibilities associated with the phase-out of coal power. Considering the inter-provincial transmission of coal and coal power, this paper constructs a novel two-layer network framework incorporating both coal mining and coal power. This method systematically assesses the contributions of coal power production and consumption to provincial employment and tax revenue, and identifies key paths of inter-provincial impact transmission for the first time. In terms of total contribution, coal mining contributes significantly more to employment and tax revenue (1.45 million jobs and 143 billion RMB) than coal power production (0.69 million jobs and 58.2 billion RMB). Spatially, employment and tax revenue related to coal power are concentrated in North China's production areas and the coastal consumption regions. Provinces like Shanxi, characterized by abundant resource reserves yet low consumption, are more exposed to socio-economic risks from other provinces reducing coal use, whereas economically developed provinces like Guangdong currently benefiting more from coal consumption, should assume corresponding responsibility in the future sustainable transition of power sector. Our analysis emphasizes the need for future policies to consider inter-provincial economic and social impacts, innovating horizontal risk compensation and shared responsibility mechanisms, to secure the interests of resource-based provinces in the just transition of China's coal power industry.