The intensification of global climate change and the resulting environmental challenges have made carbon emission control a focal point of global attention. As one of the major sources of carbon emissions, the power sector plays a critical role in accurately quantifying CO₂ emissions, which is essential for formulating effective emission reduction policies and action plans. The average CO₂ emission factor of electricity (AEF), as a key parameter, is widely used in calculating indirect carbon emissions from purchased electricity in various industries. The International Energy Agency (IEA) reported an AEF of 0.6093 kgCO₂/kWh for China in 2021, while the Ministry of Ecology and Environment of China (MEE) officially reported a value of 0.5568 kg CO₂/kWh, resulting in a discrepancy of 9.43%. This study conducts an in-depth analysis of the calculation methodologies used by the MEE and IEA, comparing them from two critical dimensions: calculation formulas and data sources, to explore potential causes of the observed discrepancies. Differences in formula components include factors such as electricity trade, the allocation of emissions from combined heat and power (CHP) plants, and emissions from own energy use in power plants. Notably, the IEA’s inclusion of CHP allocation reduces its calculated emissions by 10.99%. Regarding data sources, this study focuses on total carbon emissions and total electricity generation, revealing that the IEA’s total carbon emissions exceed those of the MEE by 9.71%. This exploratory analysis of the discrepancies in China’s AEFs provides valuable insights and a foundational basis for further research.

With the proliferation of the internet, the issue of image tampering has escalated, necessitating robust image encryption schemes. Despite the multitude of proposed image encryption algorithms, challenges such as slow computational speed, weak security, and suboptimal visibility persist. This study addresses these challenges by introducing a high-performance encryption algorithm tailored for dynamic images—QEDI (Quick Encryption Algorithm for Dynamic Images). QEDI leverages elliptic curve-based asymmetric encryption algorithms and hash algorithms. The process involves using a hash algorithm to calculate the hash of the dynamic image slated for encryption, employing the elliptic curve algorithm to generate public and private keys, and utilizing the asymmetric encryption algorithm to process the image hash, resulting in a signature ciphertext. This ciphertext is embedded into the dynamic image, completing the encryption process. To enhance the execution speed without compromising the image quality and visibility, the bit depth of the dynamic image is reduced before hash calculation, and custom information fields are encapsulated to embed the signature ciphertext into the dynamic image. Experimental evaluations, conducted within a dynamic image generation system, encompassed assessments of security, encryption algorithm execution time, and image quality. The results indicate that utilizing QEDI for dynamic image encryption yields better security compared to EDI (Encryption Algorithm for Dynamic Images). QEDI exhibits minimal impact on image quality, with a noteworthy 69.77% reduction in execution time compared to EDI. Furthermore, when compared to existing algorithms employing image conversion for encryption, QEDI-encrypted images demonstrate enhanced visibility, better image quality, and expedited encryption speed.

Quadrupole mass spectrometers are widely applied due to their compact structure, easy operation, and mature technology, which offer high economic and market competitiveness across various fields. A complete quadrupole mass spectrometer consists of components such as the ion source ionization chamber, ion optical system, and quadrupole mass analyzer. These components work together to enable qualitative and quantitative analysis. Researchers often adopt single-component simulation models rather than comprehensive ones due to the need for resource allocation and specific research goals. However, this approach has drawbacks which lead to inaccurate performance prediction in multi-component scenarios, especially in terms of the influence of fringe fields on ion trajectories. We have found that ignoring these interactions leads to an inability to accurately predict the overall system performance, especially regarding the influence of fringe fields on ion trajectories. This calls for a more sophisticated approach. To overcome these limitations and explore the optimal performance of quadrupole mass spectrometers, parameter optimization has become a crucial aspect. In this study, we developed a comprehensive quadrupole mass spectrometry simulation model integrating key components such as the electron impact ion source (EI source) ion optical system and the quadrupole mass analyzer. It covers the entire ion path, enabling the tracking of ion trajectories from the point of generation, and providing a thorough simulation of ion behavior and detailed analysis of component interactions. This capability addresses the limitations of traditional single-component simulation models, which often miss important ion dynamics behaviors. Based on this model, two distinct voltage optimization simulation experiments were conducted: staged optimization and global optimization. Staged optimization separately treats different parts while global optimization considers all components simultaneously. To address the challenges posed by numerous optimization parameters and high time costs, the orthogonal experimental design method was employed, which remarkably enhanced the efficiency of parameter optimization and reduced the experimental time and cost. The results showed that the ion transmission with the optimal voltage combination in the global optimization experiment increased by approximately 33% relative to the maximum ion transmission rate achieved in the staged optimization, indicating that global optimization can more comprehensively analyze the relationships between various voltage factors and significantly improve ion transmission efficiency. Additionally, an exploration was conducted regarding the impact of the newly introduced component (a pre-quadrupole) on the instrument’s performance. The results of this study provide valuable data support for the optimized design of quadrupole mass spectrometers, highlighting the significance of both parameter and performance optimization in improving the overall capabilities of these instruments.