In the CCUS industrial chain, the pipeline transportation of CO₂ is a crucial link that connects the upstream and downstream. However, currently, there is still no reliable, stable, and efficient method for detecting pipeline leaks. Based on the time difference in arrival (TDOA) localization method within the acoustic emission technique, this study conducted preliminary experiments on air pipeline leak localization and experiments on gaseous CO₂ pipeline leak localization, thereby establishing the applicability of acoustic emission technology for leak detection in gaseous CO₂ pipelines. In the preliminary experiment on air pipeline leak location, the SNR (signal-to-noise ratio) of the CEEMDAN denoising algorithm is greater than that of the EEMD denoising algorithm. The larger the SNR, the smaller the signal interference, which proves the superiority of the CEEMDAN denoising algorithm. In the experiment on gaseous CO₂ pipeline leak location, the CEEMDAN denoising algorithm was adopted. Five time-delay estimation methods, namely GCC, Roth weighting, PHAT weighting, ML weighting, and SCOT weighting, were used for location calculations. The positioning accuracies were 10.6%, 6.9%, 6.9%, 8.6%, and 8.6% respectively, all meeting the engineering accuracy requirements. Combining the results of the preliminary experiment on air pipeline leak location, the Roth weighting time-delay estimation method is recommended. The results show that: Acoustic emission technology can be used for the leak location of gaseous CO₂ pipelines.

Engineering corridors on the Qinghai–Tibet Plateau have substantially modified the regional ecosystem functions and environment, resulting in changes in the alpine ecosystem. In addition, the building and operation of these engineering corridors have led to rapid permafrost degradation, which in turn has impacted local vegetation along these corridors. This study investigated vegetation changes and their driving factors by the methods of coefficient of variation, correlation analysis, and GeoDetector in a 30 km wide buffer zone at each side along the National Highway G214 (G214) at the northern and southern flanks of the Bayan Har Mountains in part of the source area of the Yellow and Yangtze rivers on the southern Qinghai Plateau, West China. The following results were obtained: (1) The Normalized Difference Vegetation Index in Growing Season (NDVI_gs) rose slightly in 2010–2019, with an average annual change rate of 0.006/a. Patterns of NDVI_gs along the G214 exhibited “low at the northern flank and high at the southern flank of the Bayan Har Mountains”. (2) Spatially, average NDVI_gs increased from the first buffer zone at the distance of 0–10 km from the highway centerline to the second buffer zone at 20–30 km perpendicularly away from the G214. Furthermore, the first buffer zone had the lowest coefficient of variation, possibly due to a low vegetation recovery as a result of the greatest influence of the G214 on NDVI_gs at 0–10 km. (3) Furthermore, annual precipitation (AP) was the dominant factor for significantly (p < 0.01) and positively influencing the variations in NDVI_gs (R = 0.75, p < 0.01). Additionally, NDVI_gs was more strongly influenced by the two combined factors than any single one, with the highest q-value (0.74) for the interactive influences of AP and annual average air temperature (AAAT) and followed by that of the AP and mean annual ground temperature (MAGT) at the depth of zero annual amplitude (15 m). Evidently, the construction and operation of the G214 have directly and indirectly affected vegetation through changing environmental variables, with significant impacts on NDVI_gs extended at least 20 km outwards from the highway. This study helps better understand the environmental impacts along the engineering corridors in elevational permafrost regions at mid and low latitudes and their management.

To ensure the safety of supercritical CO₂ pipelines and address the limitations of full-scale fracture tests, such as high risk and substantial investment, software for evaluating the crack arrest toughness of CO₂ pipelines containing impurities was developed based on the Battelle Two-Curve Model (BTCM) in this study. The software is programmed in Python (v.3.12.4), with a graphical user interface (GUI) built using PyQt6 (v.6.10.0) and a three-tier architecture design. It integrates the resistance curve model and the decompression wave model. To determine the thermodynamic state of the fluid, a large property database covering pure components and various mixtures is embedded, incorporating state equations such as PR, HEOS, and GERG-2008. The software can generate pressure drop curves, decompression curves, and resistance curves. The pressure plateau can be quickly identified by examining the pressure drop curve. Whether the pipeline can achieve self-crack arrest can be rapidly judged by comparing the positional relationships between the decompression curve and the resistance curve. To verify the accuracy of the software’s calculation results, comparisons were conducted with previous decompression wave experimental data, full-scale burst test data of a CO₂ pipeline, and the international HLP model. The calculation error of the software is within 10%. The development and application of this software provide a convenient, efficient, and accurate practical tool for the calculation of crack arrest toughness and crack arrest evaluation of supercritical CO₂ pipelines.

Carbon dioxide (CO₂) is a non-toxic asphyxiant gas that, once released, can pose severe risks, including suffocation, poisoning, frostbite, and even death. As a critical component of carbon capture, utilization, and storage (CCUS) technology, CO₂ pipeline transportation requires reliable leakage detection and precise localization to safeguard the environment, ensure pipeline operational safety, and support emergency response strategies. This study proposes an inversion model that integrates wireless sensor networks (WSNs) with the Gaussian plume model for CO₂ pipeline leakage monitoring. The WSN is employed to collect real-time CO₂ concentration data and environmental parameters around the pipeline, while the Gaussian plume model is used to simulate and invert the dispersion process, enabling both leak source localization and emission rate estimation. Simulation results demonstrate that the proposed model achieves a source localization error of 12.5% and an emission rate error of 3.5%. Field experiments further confirm the model’s applicability, with predicted concentrations closely matching the measurements, yielding an error range of 3.5–14.7%. These findings indicate that the model satisfies engineering accuracy requirements and provides a technical foundation for emergency response following CO₂ pipeline leakage.

Despite a growing body of research on supercritical carbon dioxide (SCO₂) heat transfer in microchannels, comprehensive reviews remain scarce. Existing studies predominantly focus on isolated experiments or simulations, yielding inconsistent findings and lacking a unified theory or optimization framework. This review systematically consolidates recent SCO₂ microchannel heat transfer advancements, emphasizing key performance factors, degradation mechanisms, and optimization strategies. We critically analyze over 260 studies (1962–2024), evaluating the experimental and numerical methodologies, heat transfer deterioration (HTD) phenomena, and efficiency enhancement techniques. Key challenges include the complexity of heat transfer mechanisms, discrepancies in experimental outcomes, and the absence of standardized evaluation criteria. Future research directions involve refining predictive models, developing mitigation strategies for HTD, and optimizing microchannel geometries to enhance thermal performance. This work not only integrates the current knowledge but also provides actionable insights for advancing SCO₂-based technologies in energy systems.

This study aims to clarify the influence of H₂S concentration and temperature on the sulfide stress corrosion cracking (SSCC) susceptibility of 20# steel weld joints. 20# steel is a commonly selected pipe material for ground gas pipelines, and there is a risk of welds cracking after years of service. The selection of a corrosive environment is based on the working conditions of high-sulfur oil fields on site. Slow strain rate tensile (SSRT) tests were conducted under simulated high-sulfur gathering and transportation conditions across varying temperatures and H₂S concentrations. The mechanical properties, SSCC susceptibility, fracture morphology, and elemental composition of fracture surfaces were systematically analyzed. As H₂S concentration increased (5%, 7.5%, 10%) and temperature decreased (30–60 °C), the elongation after fracture and the reduction in area of 20# steel decreased, while the yield strength and SSCC susceptibility increased. The H₂S concentration range of 0–5% represented a critical sensitivity interval for the material, where elongation after fracture decreased by up to 74%. Within the 5–10% H₂S range, elongation decreased by only 2.11%, indicating a slowing trend of fracture toughness deterioration, though SSCC susceptibility still increased by 12%. Increasing the temperature from 30 °C to 60 °C reduced SSCC susceptibility by approximately 30%, confirming higher susceptibility at lower temperatures. Temperature exerts a lesser influence on material performance than H₂S concentration. Also, 20# steel remains within the SSCC brittle fracture sensitivity zone in sulfur-containing environments, necessitating strict quality control to avoid defects and stress concentrations. In high-sulfur environments (H₂S > 5%), further increases in H₂S concentration have a diminished effect on cracking susceptibility.