环境科学最新文献

{"title":"[Spatial Pattern and Source Apportionment of Dissolved Organic Matter in Quanmin Reservoir Watershed Based on Three-dimensional Excitation-emission Matrix Spectra].","authors":"Hong-Shuang Gao, Xin-Zhong Du, Yan Zhou, Yong-Xin Liao, Qiu-Liang Lei, Hong-Bin Liu, Zheng Liu","doi":"10.13227/j.hjkx.202507112","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507112","url":null,"abstract":"<p><p>The sources and composition of dissolved organic matter （DOM） in water bodies exhibit high spatiotemporal heterogeneity. Taking the Quanmin Reservoir watershed in Sichuan Province as the study area， water samples were collected from four inflow rivers and nearby pollution sources such as farmland drainage and sewage treatment plant effluents during the wet and dry seasons. Three-dimensional excitation-emission matrix spectra （3D-EEMs） combined with parallel factor analysis （PARAFAC） was used to analyze the composition， distribution characteristics， and sources of DOM in the study area. The correlation between water quality parameters and DOM parameters was further used to clarify the sources of DOM. The results showed that： ① The average concentrations of TP， NH₄⁺-N， NO₃^--N， TN， and DOC in the Quanmin Reservoir watershed were all lower in the wet season than in the dry season， and TN was the main pollutant in the watershed. ② The PARAFAC analysis identified three components in the DOM of the Quanmin Reservoir watershed， including terrestrial humic-like C1 （<i>E</i>_x/<i>E</i>_m = 360/425 nm）， visible light region fulvic-like C2 （<i>E</i>_x/<i>E</i>_m = 400/480 nm）， and microbial metabolic products C3 （<i>E</i>_x/<i>E</i>_m = 335/417 nm）. ③ The total fluorescence intensity of DOM was higher in the wet season than in the dry season. The relative abundance of terrestrial humic-like C1 was the largest in both periods， accounting for 37.40% and 37.52%， respectively. The average maximum fluorescence intensity of DOM in the two periods was in the order of Xiongjiagou River &gt; Guxian River &gt; Xixi River &gt; Motan River. ④ Based on fluorescence spectral parameters and multi-parameter correlation analysis， the three components of DOM in the Quanmin Reservoir watershed demonstrated homogeneity， and DOM was mainly of terrestrial origin， showing weak humification characteristics. Water quality parameters in different periods had different degrees of correlation with DOM components and fluorescence parameters. The research results can provide a basis for the source tracing of nitrogen and phosphorus pollutants and water environment management in the Quanmin Reservoir watershed.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5686-5696"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Analysis of the Spatiotemporal Evolution and Driving Mechanisms of Anthropogenic Carbon Emissions in the Beijing-Tianjin-Hebei Urban Agglomeration].","authors":"Ai-Bin Wu, Yuan-Yuan Kang, Mei-Ru Liu, Fu-Guo Chen, Jian-Ying Luo, Hui-Tao Shen, Yan-Jie Qin, Yan-Xia Zhao","doi":"10.13227/j.hjkx.202507186","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507186","url":null,"abstract":"<p><p>Understanding the spatiotemporal evolution and driving mechanisms of anthropogenic carbon emissions in urban agglomerations is critical for formulating regional carbon reduction policies. Based on the carbon emission factor method and multi-source remote sensing data， this study systematically analyzed the spatiotemporal evolution characteristics and driving mechanisms of anthropogenic carbon emissions in the Beijing-Tianjin-Hebei Urban Agglomeration from 2000 to 2020. The results showed that： ① The total anthropogenic carbon emissions （in terms of C） in the Beijing-Tianjin-Hebei Urban Agglomeration exhibited a fluctuating upward trend， increasing from 105.90 Tg in 2000 to 358.58 Tg in 2020. Hebei Province was the main contributor， showing significant growth. Beijing municipality's anthropogenic carbon emissions peaked in 2010 and then exhibited a downward trend， while Tianjin municipality showed a fluctuating trend of initial increase， subsequent decrease， and renewed increase. ② Regarding anthropogenic emission structure， energy consumption was the dominant contributor， while emissions from industrial processes and waste showed a clear increasing trend， and agricultural emissions remained relatively stable. ③ Spatially， anthropogenic carbon emissions displayed a clear \"core-periphery\" structure. Megacities and industrial-transportation corridors were the main concentration areas， and spatial polarization trends intensified over time. ④ Analysis of driving mechanisms revealed that economic development， urbanization， and anthropogenic carbon emission intensity were the primary influencing factors across all three areas. However， population scale and industrial structure showed regional differences： Tianjin municipality and Hebei Province were notably influenced by population growth and industrialization， while Beijing municipality experienced more significant industrial transformation. Energy intensity showed substantial emission reduction effects in Tianjin municipality and Hebei Province， but Beijing municipality's emission reduction potential was relatively lower. Additionally， the emission-reducing effect of technological innovation had not yet been effectively realized， contributing little overall to reducing anthropogenic carbon emissions. The extended STIRPAT-ridge regression model constructed in this study demonstrated strong stability and explanatory power for analyzing the driving mechanisms of regional anthropogenic carbon emissions， thus providing scientific support for precise emission reduction and differentiated carbon management strategies in the Beijing-Tianjin-Hebei Urban Agglomeration.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5207-5219"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Clean and Low-carbon Transformation Path of the Electric Power Industry in Jiangsu Province Under the Dual Constraints of Pollution Reduction and Carbon Emission Reduction].","authors":"Bo Sun, Ye-Shun Zhang, Min-Min Teng","doi":"10.13227/j.hjkx.202505298","DOIUrl":"https://doi.org/10.13227/j.hjkx.202505298","url":null,"abstract":"<p><p>Against the backdrop of rapid economic development， Jiangsu Province is confronted with the dual strategic tasks of enhancing ecological environment quality and achieving carbon peaking and carbon neutrality. As a major source of carbon and pollutant emissions， the clean and low-carbon transformation of the power industry is of critical significance. Jiangsu Province is taken as the research object in this study， with the time frame spanning from 2025 to 2060. Under the baseline policy scenario （BAU） and two policy strengthening scenarios （STE1 and STE2）， a goal programming model is constructed， with the minimization of the total cost of the electricity supply as the objective， while the dual constraints of pollution reduction and carbon emission reduction are satisfied. Through the optimization of the power generation structure， the optimal transformation path for the power industry is explored. The results are as follows： ① The evolution of power supply costs under different scenarios was characterized by significant differences. The total cost was the lowest in the BAU scenario， while it was the highest in the STE2 scenario， mainly due to high terminal costs and a slow reduction process. The cost was high in the early stage but dropped in the later stage in the STE1 scenario， with a high proportion of clean energy. ② The characteristics of differences in the energy structure were prominent. In the BAU scenario， the proportion of coal power gradually decreased to 2.4%， forming a pattern of coordinated transition between traditional and clean energy； in the STE1 scenario， the proportion of clean energy exceeded 65%， but the system stability faced challenges； and in the STE2 scenario， coal power was retained at 23.8%， which could maintain power supply resilience， but the proportion of clean energy was relatively low. ③ The speed of coal power exit and the cost of carbon capture showed an inverse correlation. In the BAU scenario， coal power was gradually phased out， and the cost of carbon capture was moderate； in the STE1 scenario， coal power was rapidly phased out， and the cost of carbon capture was basically zero； and in the STE2 scenario， the exit of coal power was delayed， and the cost of carbon capture was the highest. Scientific references for promoting the clean and low-carbon transformation of the power industry in Jiangsu Province can be provided by the research results.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5343-5354"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Impact of Low-carbon Transport Mode Conversion on Carbon Emissions in Multiple Scenarios].","authors":"Shu-Hong Ma, Yu-Xuan Deng, Chao-Jie Duan, Yu-Fei Han","doi":"10.13227/j.hjkx.202507142","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507142","url":null,"abstract":"<p><p>With the increasing demand for urban transportation， green travel has become one of the main ways for cities to reduce carbon emissions. By utilizing multi-source transportation data such as taxi GPS data， subway card usage data， and bike-sharing order data， we aim to reveal the carbon emission reduction potential of the transformation of urban public transportation travel patterns. Firstly， by extracting the driving mileage of different transportation modes， a \"bottom-up\" urban transportation carbon emission calculation model is established to fit the spatial distribution characteristics of carbon emissions from different travel modes. Combined with the implementability of carbon reduction policies， three low-carbon combined travel scenarios are proposed to evaluate the carbon reduction potential of urban public transportation in differentiated scenarios. Taking Shenzhen City as an example for verification， the results showed that taxi travel， subway travel， and shared bike travel in urban transportation had a high degree of spatial overlap， and taxi travel could be replaced by combined low-carbon travel modes. The combined travel of \"shared bikes + rail transit\" could reduce carbon emissions by up to 20.34%. The connection and transfer capacity of subway stations will affect the willingness to choose low-carbon modes. Under the travel alternative scenarios considering the differentiation of station transfer capabilities， combined travel could reduce carbon emissions by up to 13.57%. Increasing the deployment of shared electric bikes could reduce carbon emissions by up to 22.01%， which would be a further decrease of 11.21% compared with the substitution of shared bikes. The research results can provide references for optimizing transfer facilities and reducing carbon emissions in areas with higher demand.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5314-5323"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatio-temporal Evolution Patterns and Influencing Factors of the Coupling Coordination Effect Between Low-carbon Transportation and New Quality Productive Forces Development： A Case Study of the Yangtze River Economic Belt].","authors":"Yan-Fei Li, Cheng Li","doi":"10.13227/j.hjkx.202506115","DOIUrl":"https://doi.org/10.13227/j.hjkx.202506115","url":null,"abstract":"<p><p>The coordinated promotion of low-carbon transportation and the development of new quality productive forces is of great significance for advancing the green transformation of the transportation industry and promoting high-quality economic growth in the Yangtze River Economic Belt. Exploring the coupling relationship between low-carbon transportation and the development level of new quality productive forces contributes to providing both theoretical support and practical reference for high-quality transportation development. Based on panel data of 11 provinces and municipalities in the Yangtze River Economic Belt from 2012 to 2022， this study employs the entropy-weighted TOPSIS method， a modified coupling coordination degree model， exploratory spatial data analysis， kernel density estimation， the geographical detector model， and the spatio-temporal geographically weighted regression （GTWR） model to examine the spatio-temporal evolution patterns and influencing factors of the coupling coordination effect between low-carbon transportation and new quality productive forces. The results show that： ① The coupling coordination degree exhibited a continuous upward trend， evolving overall from the running-in coordination stage to the primary coordination stage. The dominant coordination types shifted from mild imbalance and marginal coordination to primary and intermediate coordination， with a spatial distribution characterized by \"high in the east and low in the west.\" ② Spatial autocorrelation analysis revealed a significant spatial clustering pattern： Upstream regions were mainly in a \"low-low\" cluster， while downstream regions remained in a \"high-high\" cluster， indicating spatial imbalance. ③ In terms of influencing factors， technological innovation， digital information development， public transportation level， economic development level， R&D human input， and R&D expenditure were identified as key drivers， with significant spatio-temporal heterogeneity in their impacts.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5324-5342"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Speciation Characteristics and Ecological Risk Assessment of Metals in Sediments of the Zhuozhang River Basin within Shanxi Province].","authors":"Qin-Wen Hou, Jie Li, Shan Jin, Peng-Gang Pei, Hai-Hua Jiao","doi":"10.13227/j.hjkx.202512115","DOIUrl":"https://doi.org/10.13227/j.hjkx.202512115","url":null,"abstract":"<p><p>The Zhuozhang River， known as the \"mother river\" of the Changzhi region， holds significant importance for water conservation and industrial/agricultural safety due to its sediment heavy metal pollution status and source investigation. This study analyzed 57 sediment samples from the northern， southern， western， and main stream sections of the Zhuozhang River to examine the occurrence and spatial distribution of six metals： As， Pb， Cr， Cu， Hg， and Cd. Metal pollution severity was assessed using the point source index （PI） and pollution load index （PLI） methods， while potential ecological risk was evaluated through the Nemerow integrated pollution toxicity （PN-T） and potential ecological risk index （RI） approaches. Principal component analysis （PCA） and correlation analysis were employed to trace metal sources. The results revealed that Pb， Hg， Cr， and Cd were diffuse pollutants， with 80.7%-100% of sampling sites exceeding Shanxi Province's soil element background values. Cu and As were point source pollutants， exceeding standards in 35.1% and 15.8% of samples， respectively. Total metal concentrations showed a gradient trend： southern source&gt;main stream&gt;western source&gt;northern source， with variation rates ranking as southern source （34.8%）&gt;western source （22.6%）&gt;northern source （19.2%）&gt;main stream （15.6%）. Mass fraction concentrations followed a gradient of Cr&gt;Pb&gt;Cu&gt;As&gt;Hg&gt;Cd， exhibiting spatial heterogeneity： The northern source had higher proportions of Cr， Pb， and Cd； the western source showed elevated Cu and Hg； and the southern source demonstrated higher As levels. The watershed was classified as mildly polluted （1.0&lt;PI≤3.0， 1&lt;PLI≤2） with low （1.0&lt;PN-T≤2.0， RI&lt;150） and moderate （2.0&lt;PN-T≤3.0， 150≤RI&lt;300） risk levels， primarily attributed to Cd （40≤EI&lt;160） and Hg （80≤EI&lt;320） contamination. The risk gradient showed a west-to-east progression： wcstern source&gt;northern source&gt;main stream&gt;southern source. Contributions from transportation sources （Pb， Cu， Cr， As， and Cd）， agricultural sources （As， Cu， and Cd）， and industrial sources （Hg， Cd， As， and Cu） accounted for 40.4%， 25.1%， and 16.1%， respectively.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5697-5707"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatio-temporal Evolution of Supply and Demand of Ecosystem Services and SSP-RCP Scenario Prediction in Hebei Province].","authors":"Wen-Tao Tian, Qin-Jun Du","doi":"10.13227/j.hjkx.202507256","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507256","url":null,"abstract":"<p><p>As one of the core economic circles in China， the Beijing-Tianjin-Hebei Region is confronted with the challenge of a sharp increase in the demand for ecosystem services during the rapid urbanization process. Urban expansion， population concentration， and industrial upgrading have led to a continuous increase in the pressure on ecological resources such as water resources， carbon sink capacity， soil retention， and biological habitats. The imbalance in regional ecological management and the contradiction between sustainable development have become increasingly prominent. Scientifically assessing and accurately predicting the dynamics of supply and demand for ecosystem services has become a key breakthrough in solving the problems of regional ecological security and sustainable development. The SD-PLUS coupling model was used to predict the land use demand in Hebei Province in the future. The supply and demand evolution laws of water conservation （WY）， carbon storage （CS）， soil conservation （SC）， and habitat quality （HQ） in the historical and future periods of Hebei Province were evaluated based on methods such as the InVEST model and spatial assignment method. The spatio-temporal patterns of supply and demand matching of four types of ecosystem services in Hebei Province from 2000 to 2070 were revealed by using the supply-demand ratio of ecosystem services， and suggestions for optimizing the balance of supply and demand of ecosystem services in Hebei Province were put forward. The results showed that there were significant differences in land use demand in Hebei Province under different SSP-RCP scenarios. However， the demand for cultivated land and water areas decreased， while the demand for construction land increased significantly. Over the past two decades， both the supply and demand of water conservation in Hebei Province have declined， while the supply and demand of soil conservation have shown an increasing trend. The supply of carbon storage has decreased， while the demand has increased. The supply and demand of habitat quality have remained relatively stable. In the future， the changes in the supply and demand of the four ecosystem services under the three different scenarios will basically continue the trends of the past two decades. Between 2000 and 2020， Hebei Province exhibited spatio-temporal heterogeneity in the matching of ecosystem service provision and requirement， accompanied by a significant supply-demand mismatch. The imbalance of supply and demand matching will intensify in different scenarios in the future.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5592-5608"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Measurement of the Industrial Pollution and Carbon Reduction Synergistic Efficiency， Spatiotemporal Transition， and Driving Factors in the Yangtze River Economic Belt].","authors":"Jin-Wei Wang, Qing-Liu Zhu, Shi-Jing Nan, Jian-Luan Wu","doi":"10.13227/j.hjkx.202510342","DOIUrl":"https://doi.org/10.13227/j.hjkx.202510342","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Achieving the synergistic effect of industrial pollution and carbon reduction is essential for promoting the comprehensive green and low-carbon transformation of the Yangtze River Economic Belt. Exploring the spatio-temporal transition and driving factors of such synergy holds important decision-making reference significance for coordinating ecological civilization construction and high-quality economic development. Based on measuring the industrial pollution and carbon reduction synergistic effect level of 110 cities at the prefecture level in the Yangtze River Economic Belt from 2003 to 2023 using the entropy weight method， the spatial and temporal jumps and driving factors are explored by employing the spatial correlation analysis， Dagum's Gini coefficient and decomposition， kernel density estimation， and geographical detector method. The results show that： ① The overall synergistic effect level of industrial pollution and carbon reduction in the Yangtze River Economic Belt presented a U-shaped evolutionary characteristic of \"first decreasing and then rising\". During the study period， the industrial pollution and carbon reduction synergistic effect level experienced a process of first decreasing and then rebounding， but the regional gap remained significant. ② The spatio-temporal differentiation characteristics of the industrial pollution and carbon reduction synergistic effect were significant. From the time series perspective， 2008 was the key node for the change of the industrial pollution and carbon reduction synergistic effect level， which showed a continuous downward trend from 2003 to 2008 and then gradually increased. From the spatial dimension， the overall Moran's &lt;i&gt;I&lt;/i&gt; from 2003 to 2023 was significantly positive， indicating a strong spatial positive correlation in the industrial pollution and carbon reduction synergistic effect level among various cities. From the perspective of spatial correlation pattern， the industrial pollution and carbon reduction synergistic effect level showed obvious spatial agglomeration characteristics， with a more prominent regional polarization trend. ③ The inter-regional net difference was the main source of regional differences in the industrial pollution and carbon reduction synergistic effect level. Dagum Gini coefficient decomposition results indicated that inter-regional differences contributed the most to the overall differences， followed by intra-regional differences. The overlap degree among different regions contributed the least， indicating that the difference in regional development level was the dominant force causing spatial differentiation. ④ Green technology innovation， financial development， and energy consumption intensity were the key driving factors for forming the spatial pattern of the industrial pollution and carbon reduction synergistic effect. Single-factor detection results showed that green technology innovation and financial development were important factors affectin","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5286-5299"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Response of Vegetation Spatiotemporal Evolution to Climate Change and Human Activities in Gansu Province from 2001 to 2021].","authors":"Lan-Lan Qi, Jing-Hua Su, Min Wang, Qing Wang, Yu-Qi Yang, Xiao-le Zhang, Meng Lu, Yi-Zong Huang, Jing-Xin Huang","doi":"10.13227/j.hjkx.202505042","DOIUrl":"https://doi.org/10.13227/j.hjkx.202505042","url":null,"abstract":"<p><p>Located in the transitional zone of three major natural regions in China， Gansu Province serves as a critical area for investigating vegetation dynamics in response to climate change and human activities， providing a scientific basis for regional vegetation conservation and ecological engineering policies. Based on normalized difference vegetation index （NDVI） data and influencing factors datasets from 2001 to 2021， this study employed Theil-Sen Median trend analysis， partial correlation analysis， spatial autocorrelation analysis， and residual analysis to systematically analyze the spatiotemporal variations of vegetation NDVI and their driving mechanisms in Gansu Province. The results indicate that： ① The mean NDVI value during the study period was 0.352， exhibiting a distinct \"high in the southeast， low in the northwest\" spatial pattern. Both the entire province and individual geomorphic units showed significant upward trends， with 74.25% of the area experiencing vegetation improvement， particularly pronounced in the Loess Plateau of Longzhong and the southern mountainous regions. ② Climatic factor analysis revealed that temperature and precipitation exerted positive effects on vegetation NDVI in over 66% of the study area， with precipitation demonstrating a stronger influence than temperature. ③ Human activities predominantly enhanced vegetation NDVI， with stable grassland and cropland areas contributing the most （cumulatively 60%）. The change rates of nighttime light （NTL） and NDVI exhibited a weak positive spatial correlation， displaying \"low-low\" clustering in the Gannan Plateau， Hexi Corridor， Qilian Mountains， and Beishan Mountains， while \"low-high\" clustering characterized the southern mountainous area of Gansu and the Loess Plateau in central Gansu. ④ Contribution analysis highlighted that human activities （70.61%） had a greater overall impact on vegetation changes than climate change （29.39%）， though spatial heterogeneity was evident-the Gannan Plateau was the only geomorphic unit where climate change dominated. These findings elucidate the differential driving mechanisms of vegetation dynamics in transitional zones and offer critical insights for optimizing regional ecological management strategies.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5065-5075"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148866929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatial Network Analysis of Coupling Coordination Between Land Use Intensity and Habitat Quality in the Loess Plateau of Northern Shaanxi].","authors":"Xue-Feng Yuan, Rui-Na Zhang, Lin-Ru Li","doi":"10.13227/j.hjkx.202507309","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507309","url":null,"abstract":"<p><p>Exploring the spatiotemporal evolution and coupling relationship between land use intensity and habitat quality is of great significance for achieving harmonious development of the human-land system and scientific management of ecosystems. This study focuses on the Loess Plateau of northern Shaanxi， a typical ecologically fragile region. It applies a coupling coordination model to evaluate the coupling relationship and coordination level between regional land use intensity and habitat quality and introduces a modified gravity model and social network analysis to interpret the spatial network characteristics of their coupling relationship. The results show that： ① The spatial pattern of land use intensity in the study area demonstrated a \"high in the central region and low in the northern and southern regions\" trend. Areas with low intensity were shrinking and aggregating， while areas with medium and high intensity were expanding and extending. The habitat quality presented a stepped distribution of \"low in the north - stable in the central region - high in the south.\" The average indices were 0.603 4， 0.603 8， 0.603 6， 0.601 5， and 0.597 3， showing a trend of first rising and then falling. ② The coupling coordination degree between land use intensity and habitat quality decreased from 0.718 in 2000 to 0.691 in 2015 and slightly rose to 0.695 in 2020， showing a trend of first fluctuating downward and then rebounding. The spatial distribution was characterized by \"high in the central region and differentiation between the north and the south，\" and the coordination differences among counties were gradually narrowing. ③ The spatial correlation of coupling coordination degree presented a pattern of \"weakening in the central region and strengthening in the north and south.\" The correlation intensity between energy-rich areas and ecological agricultural areas significantly increased， while the correlation effect in ecologically fragile zones continued to decline. ④ From 2000 to 2020， the spatial association network of coupling coordination remained stable， exhibiting characteristics of moderately low density （0.248 3-0.255 0）， full connectivity， and flattening. The network efficiency slightly increased from 0.811 6 to 0.815 2 and gradually optimized with the advancement of ecological policies. Promoting optimized network governance through zoning management and the establishment of collaborative mechanisms can facilitate the coordinated development of the human-land system in northern Shaanxi.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 8","pages":"5497-5508"},"PeriodicalIF":0.0,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148867018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}