Table of Content

20 September 2026, Volume 62 Issue 5

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Trajectory Control of Non-smooth Robotic Arms Based on the Modified Udwadia-Kalaba Method

RONG Siqi, YAO Wenli, ZHANG Xingang, ZHANG Shucui

2026, 62(5):  941-949.  DOI: 10.13209/j.0479-8023.2025.100

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To address the degradation of tracking accuracy and insufficient control stability in robotic manipulator systems involving nonsmooth effects, such as viscous and sliding friction, a servo control strategy based on the Udwadia-Kalaba (U-K) method is proposed. Within an extended U-K dynamics framework that accounts for the coupling between normal and tangential constraint forces, the desired trajectory of the controlled system is formulated as a set of servo constraints. Analytical expressions for the active control forces and passive constraint forces are then explicitly derived, based on which a corresponding servo control method is developed. This method effectively mitigates system oscillations and tracking accuracy degradation caused by the coupling of constraint forces. To further enhance system stability, the Baumgarte stabilization method is introduced to correct constraint violations induced by initial perturbations. In addition, a smoothing Newton algorithm is employed to regularize the absolute-value term arising from the determination of the normal support-force direction, thereby improving numerical stability. Simulations of various complex trajectories are conducted in MATLAB. The results demonstrate that the proposed servo control strategy effectively suppresses friction-induced oscillations while ensuring high-precision and asymptotically stable trajectory tracking, exhibiting favorable robustness and generalizability.

A Retrieval-Augmented Two-Stage Approach for Cross-Cultural Machine Translation

WANG Yingqi, YANG Yating, DONG Rui, MA Bo, TURGHUN Osman, LU Kaiwen, WANG Lei, ZHOU Xi

2026, 62(5):  950-962.  DOI: 10.13209/j.0479-8023.2026.009

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Traditional machine translation systems mainly focus on linguistic and semantic consistency but struggle to handle the ambiguity and context sensitivity inherent in cultural content. To address this, we propose a retrieval-augmented two-stage translation framework R2-MT to improve the accuracy and cultural relevance of translating culture-specific items. In the first stage, knowledge base retrieval is performed based on label similarity and description semantics to disambiguate culture-specific items and generate culturally adapted translations. In the second stage, generated translations as hard constraints are injected into the translation prompt to ensure semantic precision and cultural conformity. To support this process, we constructed a multilingual culture-specific item knowledge base covering 15 language variants and approximately 1.9 million entities, providing a foundation for entity retrieval and disambiguation. Additionally, we designed an instruction fine-tuning dataset covering 10 languages and containing 160000 samples, and jointly trained a large language model on two tasks: entity translation generation and constrained name translation, thereby enhancing the model’s ability to translate culture-specific items. Experimental results demonstrate that R2-MT significantly outperforms strong baselines on multiple cross-cultural translation benchmarks in terms of BLEU, COMET, and cultural relevance metrics. Ablation studies and human evaluations further confirm the effectiveness and complementary advantages of the two-stage mechanism in improving the translation accuracy of culture-specific items and maintaining overall translation quality. 

Multi-language Social Media Event Detection Based on Graph Completion

CHENG Xiaotian, MA Longxuan, ZHANG Kai, XIAN Yantuan, YU Zhengtao, HUANG Yuxin

2026, 62(5):  963-976.  DOI: 10.13209/j.0479-8023.2026.008

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To address the two major issues of reduced embedding similarity due to language differences in multilingual scenarios and the frequent neglect of implicit relational connections in social message graphs, a multilingual social media event detection method called MGCGNN is proposed based on graph completion. First, message embeddings are generated using pre-trained language models, and cross-lingual entity alignment is achieved via Wikipedia entity IDs to construct an initial multilingual social message graph. Subsequently, a random walk strategy is employed to capture long-range semantic associations between nodes, completing the message graph structure and thereby enhancing event clustering effectiveness. Experiments on a trilingual hybrid dataset built upon the Event2012 dataset demonstrate that the proposed method significantly outperforms baseline models, with an average NMI improvement of 4%–5%, validating higher precision and effectiveness in complex multilingual scenarios.

Automatic Evaluation of Machine Translation Incorporating Translation Difficulty

TANG Ming, LI Maoxi

2026, 62(5):  977-985.  DOI: 10.13209/j.0479-8023.2026.007

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Mainstream automatic evaluation metrics of machine translation typically treat all input sentences equally, overlooking the variation in translation difficulty posed by different source sentences. This often leads to inadequate reflection of system performance on structurally complex or lexically rare content. To address this limitation, we propose a novel evaluation approach TD_MT that integrates translation difficulty as a core factor in the scoring process. By analyzing representative samples using large language models and extracting syntactic and lexical features, such as dependency tree depth and word frequency, a linguistically interpretable, rule-based framework for translation difficulty classification is constructed. Evaluation scores are dynamically adjusted based on the estimated difficulty levels of source sentences, enabling a more nuanced assessment. At the sentence level, the proposed difficulty-aware machine translation evaluation metric exceeds the best-performing participating metric, XCOMET-Ensemble, by 0.004. At the system level, it exceeds XCOMET-Ensemble by 0.060. Experimental results on the WMT’23 benchmark dataset demonstrate that, compared with classical evaluation metrics and XCOMET-Ensemble, the proposed method achieves a significantly higher correlation with human judgments.

FE-PointRCNN: 3D Object Detection for Autonomous Driving Based on Feature-Enhanced PointRCNN

ZHANG Baowen, ZHAO Yongyong, SU Chengzhi, CAO Guohua

2026, 62(5):  986-998.  DOI: 10.13209/j.0479-8023.2026.068

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To address the challenges in autonomous driving environment perception — namely, that pure vision-based schemes are prone to misjudgment, existing 3D point cloud object detection algorithms suffer from insufficient feature representation due to the sparsity and inhomogeneity of point clouds, low detection accuracy in complex scenarios, and the fact that most algorithms only validate single-category objects, failing to meet the multi-category perception requirements of national standards — a feature-enhanced PointRCNN network (FE-PointRCNN) is proposed. To overcome the limitations of traditional MLP structures, which possess strong global feature extraction capabilities but weak local geometric feature capture, along with the high computational overhead of attention mechanisms, Enhanced Multi-Layer Perceptrons (E-MLPs) and Residual Channel Attention (RC-Attention) modules are designed. These modules are integrated to construct an improved E-PointNet++ feature extraction architecture that enables parallel multi-scale feature extraction and adaptive weighted enhancement of key channel features, thereby alleviating the gradient vanishing problem and enhancing feature discriminability. Comparative and ablation experiments are conducted on the KITTI and ONCE datasets. The results demonstrate that the proposed FE-PointRCNN achieves accuracy improvements over the baseline PointRCNN* for the Car, Pedestrian, and Cyclist categories and exhibits strong robustness on the complex-scene ONCE dataset. The proposed algorithm effectively improves point cloud feature extraction capability and multi-category object detection performance, providing valuable technical support for LiDAR-based perception systems in autonomous driving. 

Comparison of Bundle Adjustment Convergence Using Parallax-Angle and Cartesian Parameterizations for Image-Based 3D Reconstruction: Experimental Validation across over 100 Datasets

TAN Ping, DAI Yunfan, ZUO Zhengkang, GAO Yunlong, LIU Dongxia, DONG Jiaojiao, WANG Jiawei, ZHU Guihai, XU Ershuai, WANG Qiang, LU Wenyi, ZHAO Lijie, YANG Chong, LI Xiaokai, LIU Wenxuan, YANG Yang, HAN Binghong

2026, 62(5):  999-1014.  DOI: 10.13209/j.0479-8023.2026.104

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To address the problems of limited-scale comparative experiments against mainstream approaches and inconsistent optimizer configurations when applying parallax‑angle parameterization to image‑based 3D reconstruction, 106 bundle adjustment (BA) datasets were constructed spanning vehicle‑borne, UAV, and close‑range scenarios. We standardized the solution workflows for the mainstream Cartesian-coordinate parameterization (SBA) and parallax-angle parameterization (PBA) methods to ensure a fair comparison. The two methods were systematically evaluated in terms of convergence, computational time, image-space accuracy, and parameter-space accuracy. The experimental results showed that, across the 106 paired datasets, PBA generally required significantly fewer iterations than SBA, exhibiting a faster convergence trend. In representative scenarios with relatively large initial point-cloud noise or divergence of the Cartesian-coordinate method, PBA yielded more stable optimization results in both image and parameter spaces. The datasets and source code are publicly available at https://reurl.cc/OmZz09 and https://github.com/Polar-vision/PBA-V3. 

Background Noise Suppression for Vibroseis Based on Non-stationary Signal Decomposition

QIAN Yian, ZENG Tongsheng, HU Tianyue, ZENG Qingcai

2026, 62(5):  1015-1024.  DOI: 10.13209/j.0479-8023.2026.054

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This paper proposes a background noise suppression technique for vibroseis data based on non-stationary signal decomposition. Taking the time-frequency correlation between sweep signals and effective signals as prior constraints, a non-stationary signal decomposition model is constructed. The orthogonal matching pursuit algorithm is adopted to realize the adaptive separation of effective signals and complex background noise, thereby breaking the limitation of traditional methods that assume stationary noise. Tests on synthetic data verify that the proposed method can effectively extract uncorrelated effective vibroseis signals amid complex noise environments. Applications to field seismic data acquired from the Gobi area of the Tarim Basin with low signal-to-noise ratio further demonstrate that this method outperforms the frequency-wavenumber predictive filtering method in background noise attenuation. The processed seismic sections feature improved event continuity and elevated overall signal-to-noise ratio.

High-Resolution Sedimentary Layer Thickness Model and Seismic Vulnerability Assessment of Shanghai Based on HVSR Measurements and Dense Observation Arrays

TAN Junqing, HE Lipeng, GE Zengxi, LUO Bin, REN Pengfei, GUO Zhen

2026, 62(5):  1025-1034.  DOI: 10.13209/j.0479-8023.2026.095

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Based on the ambient noise horizontal to vertical spectral ratio (HVSR) technique and dense seismic array observations, combined with geological borehole data, an empirical formula for estimating sedimentary layer thickness in Shanghai is established, and a high-resolution sedimentary layer thickness model is constructed. The model shows a strong correlation with the regional geological structures of Shanghai and effectively characterizes the spatial variations of sedimentary layer thickness. Furthermore, the seismic vulnerability index of Shanghai is analyzed using the HVSR technique, and a seismic vulnerability distribution map is obtained. The results provide new constraints on the tectonic evolution and fault systems of Shanghai and offer scientific basis and technical support for seismic hazard mitigation, urban planning, and seismic design.

Characteristics and Controlling Factors of Movable Fluid Occurrence Based on Multistage Centrifugal Nuclear Magnetic Resonance Experiments

WANG Zhelin, LÜ Xinrui, LU Kai, WU Xinwei, GUO Yanjun

2026, 62(5):  1035-1045.  DOI: 10.13209/j.0479-8023.2026.036

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To overcome the limitations of using a single T₂ cutoff value for characterizing fluid occurrence and mobility in reservoirs, a method based on multistage centrifugal nuclear magnetic resonance (NMR) experiments is proposed to determine multiple T₂ cutoff values. This method is used to identify fluid types and their distribution characteristics. Combined with constant‑rate mercury intrusion porosimetry and X‑ray diffraction (XRD) analysis, the pore structure and mineral composition of the reservoir are determined, and the occurrence characteristics and controlling factors of movable fluids in the multiscale pore spaces of unconventional reservoirs are investigated. The results indicate that the division method with multiple T₂ cutoff values further subdivides the types and occurrence spaces of movable fluids. The mobility evaluation can better reflect the development characteristics of micron‑nano pore throats and the mineral composition within the reservoir, and shows stronger adaptability to shale and tight sandstone reservoirs, which have more subtle pore structures and more complex mineral compositions. The occurrence characteristics of movable fluids are jointly controlled by three main factors: reservoir physical properties, mineral composition, and the uniformity of pore‑throat distribution.

Genesis of Siliceous Deposits in the Upper Cambrian Succession in the Western Margin of Northern Tarim Basin

SHI Lei, XU Haoran, WANG Xiaoxue, WANG Ping, ZHU Biqing, ZHANG Liang, HE Yanxin, GUAN Ping

2026, 62(5):  1046-1054.  DOI: 10.13209/j.0479-8023.2026.096

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The origin of siliceous material in dolostones of the Upper Cambrian Lower Qiulitage Formation in the western margin of Northern Tarim Basin was investigated using germanium/silicon (Ge/Si) ratios together with major- and trace-element geochemistry. The dolostones contain 65.40%–99.49% SiO₂ (mean value > 90%) and yield Ge/Si ratios of 0.12–2.74 μmol/mol (mean value = 0.54 μmol/mol), far below typical hydrothermal end-member values of 4–25 μmol/mol; samples close to the Mana igneous body show elevated ratios. Ge/Si correlates positively with Fe₂O₃ but shows no relationship with Al₂O₃. Taken together, the low Ge/Si ratios and low Al₂O₃ contents indicate that the silica precipitates mainly from residual seawater and is subsequently overprinted, to a limited extent, by hydrothermal fluids that produced vein-hosted aggregates. Al₂O₃ contents increase systematically from east to west across the study area, pointing to a westward decrease in hydrodynamic energy that favours the accumulation of fine-grained terrigenous detritus on the restricted platform. These findings place important geochemical constraints on the silica provenance and diagenetic history of the Lower Qiulitage dolostone reservoirs and have implications for deep hydrocarbon exploration.

Panoramic Overview and Prospects of China’s Natural Hydrogen Research: An In-Depth Analysis Based on Knowledge Graph

LI Huayang, LIU Quanyou, ZHANG Chi, ZHU Dongya, WU Xiaoqi, SHI Zehui, CHEN Jiaao, RUAN Yongqi, CHEN Fuzhi

2026, 62(5):  1055-1073.  DOI: 10.13209/j.0479-8023.2026.020

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Using knowledge mapping and bibliometric methods, this study delivers a systematic and holistic analysis of natural hydrogen research in China. We conduct a multidimensional review of 119 relevant publications from the China National Knowledge Infrastructure (CNKI) covering 2015 to 2025, to characterize the full research landscape, developmental trajectory, research hotspots, collaboration networks, and geographic distribution patterns. The findings show that 2023 marked the onset of explosive growth in China’s natural hydrogen research, fueled by a confluence of drivers: global energy transition pressures, national carbon neutrality policies, and rising recognition of white hydrogen (also called gold hydrogen) as a viable hydrogen energy resource. Research institutions follow a geographic pattern of concentrated core hubs alongside dispersed sites nationwide. Beijing has emerged as the central research hub due to its resource advantages, though clear regional imbalances remain. Four types of entities — universities, energy enterprises, seismological bureaus, and geological survey agencies (represented by Peking University and the PetroChina Research Institute of Petroleum Exploration & Development), have built a collaborative framework integrating government, industry, academia, research, and practical application. Author collaborations form a multi-center, multi-level structure. Core researchers including Jin Zhijun play a pivotal leading role, and the author collaboration network has expanded and grown increasingly sophisticated over time. The natural hydrogen research paradigm has undergone a fundamental shift: early work focused on trace hydrogen monitoring as a secondary diagnostic indicator, while modern research centers explicitly on its energy and resource value. Research priorities have shifted from early themes of soil gas, fault activity, and earthquake precursors to energy-focused topics such as serpentinization, water–rock interactions, and carbon neutrality. This transition reflects the field’s evolution from fragmented observational descriptions to the development of systematic hydrogen accumulation theory and exploration of engineering applications. Finally, we outline the potential and necessity of interdisciplinary, cross-sector natural hydrogen research. By benchmarking its research trajectory and technical framework against those of natural gas and helium, we propose establishing an interdisciplinary research system centered on the concept of “hydrogen system science”. 

Travel Carbon Emission Patterns and Equity Analysis of Public Transportation at Street Scale

ZHENG Jiangpeng, BAO Yi, HUANG Zhou, WU Lun

2026, 62(5):  1074-1088.  DOI: 10.13209/j.0479-8023.2026.098

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To address the limitations of existing studies regarding analytical scales and the exploration of social equity issues, an accounting–analysis–application framework is constructed to uncover the travel carbon emission patterns of urban public transportation. Based on Beijing’s smart card data, a bottom-up accounting model for travel carbon emissions at the street scale is developed. Through a three-dimensional equity system (vertical, horizontal, and spatial), the relationships between emission characteristics and socioeconomic factors are analyzed, and multi-scenario shared bicycle substitution schemes are designed to evaluate the emission reduction potential. The results show that travel carbon emissions exhibit distinct spatiotemporal patterns characterized by tidal polarization on weekdays, multi-core dispersion on holidays, and a mixed transition on rest days. Equity analysis reveals a significant phenomenon of environmental cost shifting: during peak hours, low-housing-price areas contribute half of the total travel carbon emissions, with per capita emissions 72% higher than those in high-housing-price areas, resulting in a spatial lock-in effect of low-income–high-emission and high-income–low-burden. Furthermore, shared bicycles demonstrate the optimal emission reduction effect for medium-distance trips of 2–4 km; scenario synergy can achieve an emission reduction of 4.24% and effectively promote transport environmental equity by precisely alleviating the carbon burden in peripheral communities. This study provides a systematic analytical framework and fine-grained policy references for the equitable, low-carbon transition of urban transportation.

Interaction between Dissolved Organic Matter and Heavy Metals Based on Bibliometric Analysis

LUO Junxi, WANG Yuan, FU Zhenghui, LI Zheng, ZHANG Lan, LI Wei

2026, 62(5):  1089-1102.  DOI: 10.13209/j.0479-8023.2026.050

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Based on the Web of Science (WoS) core collection and the China National Knowledge Infrastructure (CNKI) database, 2485 English publications and 232 Chinese publications in the research field of interactions between dissolved organic matter (DOM) and heavy metals from 2004 to 2024 were screened. Using bibliometric methods combined with visualization tools including VOSviewer and CiteSpace, this study quantitatively analyzes the publication trends, scientific collaboration networks, research hotspots, and evolutionary characteristics of research frontiers in this domain.The results indicate that the global annual publication output in this field shows a continuous growth trend from 2004 to 2024. China occupies a dominant position with a share of 49.54%, and an international scientific research collaboration network centered on China has been formed. The core research issues in this field focus on the complexation-adsorption mechanisms of heavy metals driven by DOM functional groups, as well as the regulatory patterns of DOM fractions, environmental factors and microbial activities on the migration, transformation and bioavailability of heavy metals. Cutting-edge technologies represented by high-resolution mass spectrometry and in-situ spectroscopic characterization have become the main development direction for the elucidation of microscopic mechanisms in this field. By constructing a bibliometric analysis framework supported by multi-source database collaboration, this study clarifies the development stages of the field and the disparities between Chinese and international research, and accurately identifies the current bottleneck issues. The findings can provide data support and theoretical guidance for the transformation of the heavy metal pollution governance technical system from end-of-pipe control to the technical paradigm of “source regulation-process interception-resource recovery”, and also offer a reference for the future layout of research in this field. 

Impact of Rural Settlement Fragmentation on Land-Use Efficiency and Its Gradient Differentiation: A Case Study of Tianjin

ZHANG Bailin, ZHANG Yining

2026, 62(5):  1103-1112.  DOI: 10.13209/j.0479-8023.2026.106

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Using Tianjin as a case study, this study systematically evaluates the impact of the fragmentation of rural settlements on land-use efficiency and its gradient effects, from the dual perspectives of topographic and econo-mic gradients, based on approaches including landscape pattern indices and the geographically weighted regression model. The results show that: 1) Rural settlements in Tianjin are predominantly characterized by medium to high levels of fragmentation, displaying a concentric spatial pattern of gradual increase from the city center to the periphery, with relatively lower fragmentation in the Peri-urban Area and the Binhai New Area, and higher fragmentation in the Jizhou mountainous area and outer suburban area. Their land-use efficiency is mainly at medium to low levels, showing an opposite spatial pattern to fragmentation, declining gradually from the peri-urban area to the outer suburban area and the Jizhou mountainous area. 2) A significant correlation is observed between the fragmentation of rural settlements and land-use efficiency. Specifically, patch density, splitting index, and landscape shape index are negatively correlated with the land-use efficiency of rural settlements, whereas Mean Patch Area is positively correlated with it. 3) The impact of rural settlement fragmentation on land-use efficiency exhibits significant spatial non-stationarity. The effect is the strongest in areas with low topographic gradients, followed by areas with high topographic gradients, and relatively weaker in areas with moderate topographic gradients, while the impact intensity gradually decreases with increasing economic gradients. The research results can provide a theoretical basis for implementing rural settlement reconstruction and village planning. 

Impact of Urbanization and Ecological Construction on Conflicts among Production-Living-Ecological Spaces: A Case Study of Wuhan and Shiyan Cities

LIU Chao, TANG Yining, HONG Xia, YANG Shuangyu

2026, 62(5):  1113-1126.  DOI: 10.13209/j.0479-8023.2026.071

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Wuhan and Shiyan cities in Hubei Province were selected as comparative cases. A landscape ecological risk assessment model was constructed to evaluate the level of conflicts among production-living-ecological spaces (PLES) and their spatiotemporal characteristics. A spatial error model was then used to investigate the impact effects of urbanization and ecological construction on PLES conflict. We further analyzed the moderating role of ecological construction in mitigating such conflicts during urbanization. The study reveals that from 2000 to 2020, Wuhan was dominated by production-ecological space, while Shiyan was characterized by ecological-production space. In Wuhan, the PLES conflicts showed a “core-periphery” structural characteristic, with the conflict level gradually intensifying and predominantly characterized by moderate and weak conflict types. In Shiyan, the conflicts exhibited a pattern of higher in the north and lower in the south, with conflict levels trending downward and the proportion of weak conflict types continued to increase. Economic urbanization helped alleviate conflicts in both cities, while land urbanization exacerbated the conflict levels. Population urbanization mitigated conflicts in Wuhan but intensified in Shiyan. Furthermore, ecological development in Wuhan strengthened the exacerbating effect of land urbanization on PLES conflicts, while in Shiyan it enhanced the mitigating effect of economic urbanization and the intensifying effect of population urbanization. The research findings provide scientific evidence for formulating differentiated optimization strategies in territorial space development and protection patterns in different types of cities.

Compliance Game in the United Nations Convention to Combat Desertification: A View of Funding

LI Haoyang, LIU Shuaifei, GAO Guanglei, DING Guodong, ZHAO Yuanyuan, YU Minghan, ZHANG Ying, XU Yang

2026, 62(5):  1127-1140.  DOI: 10.13209/j.0479-8023.2026.090

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Against the backdrop of funding challenges in the implementation of the United Nations Convention to Combat Desertification (UNCCD), to conduct an in-depth analysis of the financial game dynamics between developed and developing countries and explore effective pathways for optimizing financial cooperation mechanisms, this study draws upon the “Global Public Goods” theory and the principle of “Common but Differentiated Responsibilities”, employing a combined methodological approach of comparative case analysis, static evolutionary game modeling, and numerical simulation analysis. It systematically examines the financial game dynamics, dissects the financial interaction mechanisms, and verifies the stability of game equilibria and their evolutionary pathways. The results indicate that national interests and international public opinion pressure are core factors affecting strategic choices. Developed countries choose “active cooperation” or “passive cooperation” in financial aid based on their interests and public pressure, while developing countries choose between “action” and “inaction” based on public pressure. The higher a developed country’s international reputation and environmental benefits, the more likely it is to “actively cooperate”. The greater the international reputational loss a developing country incurs, the more it is spurred to “act”. Developed and developing countries need to find a long-term stable equilibrium in funding games to realize rational allocation and efficient utilization of resources. This research offers a theoretical basis for targeted desertification funding policies and contributes to advancing global desertification governance. 

Carbon Sequestration Effects from the Grain for Green Program in Guangxi

CAO Ledan, WU Xiuqin, ZHOU Jinxing, CAO Jianhua, YANG Hui

2026, 62(5):  1141-1149.  DOI: 10.13209/j.0479-8023.2026.057

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To support targeted policy‑making for the Grain for Green Program (GFGP) in karst regions, taking Guangxi as an example, this study employs cropland utilization transfer matrices, ArcGIS spatial analysis, and centroid migration models to measure the spatial differentiation patterns and evolutionary characteristics of the carbon sequestration effects of the GFGP from 2000 to 2022. The results show that 1) carbon sequestration in project implementation areas increased significantly, with an average carbon sequestration increment of 393.92 gC/m². Spatially, it exhibited a dual-core agglomeration pattern of “central karst core area–southern coastal contiguous area”. The centroid of carbon sequestration shifted northward as the policy implementation gradually tilting towards ecologically fragile karst areas. 2) Carbon sequestration effects varied significantly among different GFGP conversion types. Conversion to shrubland emerged as the optimal pathway, with the highest average carbon sequestration increment of 483.74 gC/m². 3) Significant spatial differentiation in carbon sequestration effects existed between karst and non-karst areas. High-value carbon sequestration areas in non-karst regions were continuously distributed, while in karst regions, high-value areas were scattered and significantly constrained by site conditions. Shrub and grass restoration performed well in karst areas, whereas forest restoration exhibited a relatively weaker carbon sequestration effect due to geological limitations. Vegetation types for the GFGP should be configured according to local conditions, and differentiated management should be strengthened to enhance carbon sequestration benefits.

Research Progress and Prospects of Groundwater Background Levels Assessment Methods

YUAN Ziting, GENG Wenjing, WANG Qi, DONG Ruihai, HE Wei, HOU Qinxuan, GUO Haiquan, HUANG Guanxing

2026, 62(5):  1150-1166.  DOI: 10.13209/j.0479-8023.2026.044

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This review systematically summarizes the evolution of the concept of groundwater background levels and discusses the transition from the traditional concept of static background values to the contemporary concept of dynamic background levels. Based on this framework, existing assessment approaches are classified into five categories: empirical methods, statistical methods, pre-screening methods, data-driven methods, and integrated assessment methods. Their theoretical basis, applicability, advantages, and limitations are comparatively evaluated, and representative case studies are synthesized to illustrate their practical applications and methodological evolution. The review indicates that groundwater background assessment is shifting from conventional statistical identification toward integrated frameworks that combine multi-source data fusion, hydrogeochemical process constraints, and intelligent data-driven models. Despite substantial methodological advances, several challenges remain, including the quantitative separation of geogenic and anthropogenic contributions, insufficient characterization of the spatiotemporal variability of groundwater background levels, and limited transferability of assessment methods across regions with contrasting hydrogeological settings. Future research should strengthen the integration of hydrogeochemical process-based understanding with data-driven modeling, establish regional groundwater background databases supported by long-term monitoring networks, and promote the transition of groundwater background levels from research-oriented reference values to regionalized and dynamic benchmarks for environmental management. These efforts will provide a more robust scientific basis for groundwater contamination identification, environmental risk management, and the sustainable utilization of groundwater resources. 

Research Progress in Carbon-Based Composite Phase Change Energy Storage Materials

XIAO Li, LU Xinyue, LIU Fang, SHANG Nuo, WANG Qi, CHEN Ruiying, TANG Ying, CAO Anyuan

2026, 62(5):  1167-1176.  DOI: 10.13209/j.0479-8023.2025.090

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This review comprehensively summarizes the research progress of high-performance carbon-based composite phase change energy storage materials (PCESMs) derived from traditional and emerging carbon materials. It first introduces the characteristics of carbon materials and their reinforcement effects on phase change materials, and points out the unique advantages of emerging carbon nanomaterial aerogels compared with traditional carbon materials. This paper then discusses the preparation methods of carbon-based PCESMs and their applications in important fields such as phase change heat storage and cold storage. Finally, the future research directions of carbon-based PCESMs and novel gel composites are prospected.