环境科学最新文献

{"title":"[Effect and Mechanism of New Quality Productive Forces on Green Total Factor Productivity].","authors":"Peng Zhang, Xiao-Yu Shi, Li-Na Xin, Sheng-Fu Yang","doi":"10.13227/j.hjkx.202506298","DOIUrl":"https://doi.org/10.13227/j.hjkx.202506298","url":null,"abstract":"<p><p>Understanding the effect and mechanism of new quality productive forces （NQPF） on green total factor productivity （GTFP） is crucial for improving regional green development policies and promoting synergy between economic growth and environmental sustainability. Using panel data from 30 provincial-level administrative regions in China from 2012 to 2022， this study employs two-way fixed effects models， mediation effect models， and threshold regression models to systematically investigate the effects， transmission mechanisms， and regional heterogeneity of NQPF on GTFP. The results showed that NQPF significantly enhanced GTFP， and this conclusion remained robust under multiple tests. Technological innovation and resource allocation efficiency served as important mediating channels through which NQPF indirectly enhanced GTFP. When technological innovation or resource allocation efficiency surpassed certain thresholds， the marginal effect of NQPF on GTFP significantly increased， revealing a nonlinear escalation pattern. Moreover， the positive effect varied significantly across regions， being more pronounced in eastern， non-resource-based， and clean energy-dominated provinces， with stronger marginal effects. The findings suggest that future efforts should strengthen the synergy between technological innovation and resource allocation， implement region-specific green development strategies， and improve cross-regional green cooperation mechanisms to jointly enhance NQPF and GTFP， thereby supporting high-quality development.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6082-6092"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012409","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":"[Effect of Biochar Addition on the Microbial Community Structure of Acidic Purple Soils Developed from Different Parent Materials].","authors":"Meng Chen, Jie Lu, Yu-Xi Guo, Juan Huang, Zi-Fang Wang, Wen-Cai Dai, Ming Gao","doi":"10.13227/j.hjkx.202507099","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507099","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Soil microorganisms are central to the material cycle in terrestrial ecosystems， and their community composition， diversity， and stability are key indicators of soil health and sustainability. Due to its unique physicochemical properties， biochar has shown potential advantages in improving acidic purple soils by enhancing soil fertility and regulating soil acidity. To investigate the effects of biochar on the improvement and microbial community structure of acidic purple soils derived from different parent materials， an indoor incubation method was adopted. Four types of acidic purple soils widely distributed in the Sichuan Basin， derived from the Shaximiao Formation， Jiaguan Formation， Penglaitown Formation， and Suining Formation， were selected as research subjects. An equal amount of biochar was added to each soil type， followed by a 63-day indoor incubation. Soil bacterial and fungal communities were measured using indoor analysis and high-throughput sequencing. The study investigated the effects of biochar on available nitrogen， base cations， and the composition and diversity of microbial communities in different acidic purple soils under the same conditions. The results showed that： ①The contents of NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;-N and base cations increased in all acidic purple soils with biochar addition， while the contents of NH&lt;sub&gt;4&lt;/sub&gt;&lt;sup&gt;+&lt;/sup&gt;-N， exchangeable hydrogen （Q&lt;sub&gt;H&lt;sup&gt;+&lt;/sup&gt;&lt;/sub&gt;）， and exchangeable aluminum （Q&lt;sub&gt;Al&lt;sup&gt;3+&lt;/sup&gt;&lt;/sub&gt;） decreased. ②After biochar application， bacterial &lt;i&gt;α&lt;/i&gt;-diversity was highest in the acidic purple soil from the Suining Formation， while fungal &lt;i&gt;α&lt;/i&gt;-diversity was highest in the acidic purple sandy soil from the Jiaguan Formation. ③After biochar application， the relative abundance of &lt;i&gt;Bacillus&lt;/i&gt; was highest in the acidic purple soil from the Shaximiao Formation， while &lt;i&gt;Sphingomonas&lt;/i&gt; was most enriched in the acidic purple soil from the Suining Formation. In the fungal community， the relative abundance of &lt;i&gt;Chaetomium&lt;/i&gt; was highest in the acidic purple soil from the Shaximiao Formation， and &lt;i&gt;Fusarium&lt;/i&gt; was most enriched in the acidic purple sandy loam from the Penglaitown Formation. Based on microbial network feature analysis， the bacterial network in the acidic purple soil from the Shaximiao Formation was more complex， while the fungal network in the acidic purple sandy loam from the Penglaitown Formation was more complex. ④Correlation and redundancy analyses showed that soil organic matter （SOM） and total nitrogen （TN） were the main factors influencing the bacterial community structure， while the carbon-to-nitrogen ratio （C/N）， SOM， and available phosphorus （AP） were the main factors influencing the fungal community structure.Due to the differences in their material composition and physicochemical properties， the addition of the same amount of biochar resulted in significant variations in the soil microbial community structure among the different acidic purp","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6516-6529"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012506","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":"[Prediction of Ecosystem Service Evolution and Trade-off/Synergy Analysis in the Yangtze River Delta Region].","authors":"Wei-Dong Zhang, Bin Dong, Pei-Zhen Zhu, Cong-Ge Peng, Hao Wang, Jian-Shen Qu, Yue-Xia Han","doi":"10.13227/j.hjkx.202505359","DOIUrl":"https://doi.org/10.13227/j.hjkx.202505359","url":null,"abstract":"<p><p>Ecosystem services（ES） play a critical role in the context of high-quality ecological development in the new era. This study focuses on the Yangtze River Delta Region as the study area， employing the InVEST model to assess four key ecosystem services from 1990 to 2020， analyzing their spatiotemporal evolution patterns. Using the geographical detector model， we identify the dominant driving factors behind the spatial heterogeneity of these services. Additionally， GeoDa software is applied to conduct an in-depth analysis of the trade-offs and synergies among different ecosystem services. Finally， the PLUS model is utilized to simulate and predict the spatial distribution patterns of ecosystem services in 2030 under various development scenarios. The results showed： ① From 1990 to 2020， in the Yangtze River Delta Region， carbon storage and habitat quality were generally higher in the south and lower in the north and central areas. Food production， conversely， was higher in the north and lower in the south. Both habitat quality and soil conservation exhibited a distribution pattern with higher values in the south and southwest and lower values in the north. Water yield was primarily concentrated in the mountainous areas of Zhejiang and southern Anhui. ② Topography and elevation were the key factors influencing changes in carbon storage and soil conservation function， and population density was the key factor influencing changes in habitat quality， while annual precipitation was the primary driver influencing changes in water yield. Apart from topographic factors， precipitation and population density were the key factors influencing grain production. ③ Compared to the baseline year of 2020， the study area exhibited the following changes in ecosystem services under different scenarios： Under the natural development scenario， water yield and habitat quality increased， while carbon storage and soil retention decreased. Under the ecological protection scenario， carbon storage， water yield， and habitat quality all showed improvement. Finally， under the cropland protection scenario， carbon storage and soil retention increased， whereas water yield and habitat quality declined. This study provides valuable insights into the complex dynamics of ecosystem services in rapidly urbanizing regions， offering a scientific basis for regional ecological planning and sustainable development strategies.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6353-6364"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012911","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 Pattern and Mechanisms of Digital Ecological Civilization Construction in China].","authors":"Xian-Feng Han, Ya-Nan Gou","doi":"10.13227/j.hjkx.202507103","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507103","url":null,"abstract":"<p><p>Scientific understanding of the construction level， spatial and temporal patterns， and mechanisms of digital ecological civilization is of great significance for the country to accelerate the construction of a green and intelligent digital ecological civilization （DEC） under the new development pattern. This study， based on panel data from 282 prefecture-level cities in China from 2011 to 2022， employed the Dagum Gini Coefficient， Gaussian kernel density estimation， club convergence test， and the quadratic assignment procedure to analyze the construction level， spatio-temporal pattern， and mechanisms of DEC. The findings reveal： ① Although the comprehensive index of China's DEC construction level and its subsystem indices remained relatively low， they showed a steady upward trend. ② Significant regional differences existed in the construction level of DEC across the nation and within the eight major economic zones. The main source of differences was hyper-variation density， with inter-regional differences playing a secondary role， and intra-regional differences having the minimal effect. ③ While maintaining certain commonalities， the national and eight economic zones' kernel density distribution curves also exhibited obvious regionally differentiated characteristics. During the sample period， the level of DEC construction nationwide and across regions exhibited an upward trend， with widening regional gaps. Except for in the northwest region， polarization phenomena existed nationwide and in other regions. ④ Urban DEC construction remained imbalanced， and cities showed significant spatial differentiation. Across the nation and within the eight major economic zones， high-level city clusters led a gradient development pattern， and other cities continually caught up. ⑤ The basic conditions， construction support， and construction effectiveness of DEC all had significant positive impacts on differences in digital ecological civilization construction， with construction effectiveness having the largest impact coefficient， making it the primary source of differences. Additionally， enhancing the spatial coordination in urban development and st rengthening differentiated financial services helped narrow regional differences in digital ecological civilization construction. Notably， various driving factors exhibited significant heterogeneity across different comprehensive economic zones. This study provides important insights for effectively advancing DEC construction. The government should fully leverage the demonstrative and leading role of high-performing regions， guide different regions to explore differentiated paths for DEC construction based on their unique characteristics， and implement gradient-based policy support according to the development stages of different regions.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6405-6421"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012923","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 Mechanism of the Spatial Correlation Network of Digital-real Economy Integration on the Synergy of Pollution and Carbon Emission Reduction].","authors":"Zheng Li, Kai Wang, Jia-Xin Tan, Chang Gan","doi":"10.13227/j.hjkx.202508023","DOIUrl":"https://doi.org/10.13227/j.hjkx.202508023","url":null,"abstract":"<p><p>Against the backdrop of digital-intelligent transformation， exploring the effects and mechanisms of the spatial correlation network of digital-real economy integration on the synergy of pollution and carbon emission reduction holds significant practical implications for promoting the coordinated advancement of ecological civilization construction and high-quality development. Using the modified gravity model， social network analysis， and econometric regression model， this study examines the influence mechanism of the spatial correlation network of digital-real economy integration in China's provinces on the synergy of pollution and carbon emission reduction from 2011 to 2022. The results indicate that： ① The spatial correlation of digital-real economy integration in China exhibited an increasingly complex \"multi-center driven\" network structure， presenting a layered differentiation pattern that decreased from east to west and from inner to outer regions. ② The spatial correlation network of digital-real economy integration could significantly promote the synergy of pollution and carbon emission reduction. Compared with that in the eastern region， non-pilot provinces， and service-oriented provinces， the spatial correlation network of digital-real economy integration in the central-western regions， pilot provinces， and production-oriented provinces exerted a stronger promoting effect on the synergy of pollution and carbon emission reduction. ③ The spatial correlation network of digital-real economy integration exerted positive impacts on the synergy of pollution and carbon emission reduction by promoting technological progress， driving economic agglomeration， and reducing energy intensity. Both human capital investment and public environmental attention strengthened the promoting role of the spatial correlation network of digital-real economy integration in the synergy of pollution and carbon emission reduction. The findings provide theoretical support and practical references for formulating collaborative emission reduction strategies and achieving the synergy of pollution and carbon emission reduction.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6070-6081"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012879","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":"[Spatiotemporal Characteristics and Influencing Factors of Fossil Energy Carbon Emissions in Sichuan Province].","authors":"Hong-Yang Ren, Bo-Ting Zhang, Yang Gao, Lei Yang, Ruo-Lan Du, Xi Li, Bing Wang","doi":"10.13227/j.hjkx.202503163","DOIUrl":"https://doi.org/10.13227/j.hjkx.202503163","url":null,"abstract":"<p><p>To characterize the spatiotemporal evolution pattern and driving mechanisms of fossil energy carbon emissions in Sichuan Province， a carbon emission accounting framework covering energy extraction， transmission， and consumption stages was established. By integrating local Moran's <i>I</i>， LISA spatiotemporal clustering， and center of gravity migration methods， the study revealed the regional aggregation and dynamic migration features of carbon emissions. Furthermore， the STIRPAT model was combined with Pearson correlation analysis， ridge regression， and random forest methods to identify key driving factors. The results showed that：① Fossil energy carbon emissions in Sichuan Province exhibited a fluctuating upward trend， dominated by the energy consumption stage. ② Significant spatial heterogeneity and temporal differentiation were observed， with the northwest-southeast spatial distribution pattern of carbon emission， and the core of emission migrating northward， reflecting a transition from a \"resource-based\" to an \"industry-based\" regional pattern. Meanwhile， local aggregation intensified， with \"high-high\" clusters expanding from the early Panxi Region to the southern Sichuan Province urban agglomeration， resulting in increasingly prominent regional clustering. ③ From 2011 to 2021， Sichuan generally experienced weak decoupling， with carbon emission growth lagging behind GDP growth and improving emission efficiency. ④ Carbon emissions were strongly positively correlated with urbanization rate， freight turnover， GDP， and energy consumption （|<i>r</i>|0.63-0.94）， with extraction， transmission， and end-use consumption stages primarily driven by energy scale， logistics expansion， and economic and demographic factors， respectively.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6000-6013"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012941","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 Spatial-temporal Pattern and Influencing Factors of the Coordinated Development of Carbon Reduction， Pollution Reduction， and Green Expansion in the Yellow River Basin].","authors":"Hong-Hong Liu, Jia-Yun Zhang","doi":"10.13227/j.hjkx.202507113","DOIUrl":"https://doi.org/10.13227/j.hjkx.202507113","url":null,"abstract":"<p><p>The collaborative promotion of carbon reduction， pollution reduction， and green expansion is an important method for achieving the \"dual carbon\" goals and ecological civilization strategy in the Yellow River Basin. Clarifying the spatiotemporal pattern and influencing factors of the synergy level of carbon reduction， pollution reduction， and green expansion is the basis for policy formulation. On the basis of clarifying the synergistic and mutually beneficial relationship between carbon reduction， pollution reduction， and green expansion growth， a comprehensive evaluation system for the carbon reduction， pollution reduction， and green expansion composite system was constructed using 54 prefecture level cities in the Yellow River Basin as the research object. The level of collaborative development was measured using a three-dimensional space vector model， describing the dynamic evolution of collaborative development through kernel density estimation methods， and combining Geodetectors to analyze the influencing factors of collaborative development. The results show that： ① The level of coordinated development in the Yellow River Basin was on the rise， while regional heterogeneity was evident. The level of coordination among upstream cities was higher than that among midstream cities， while downstream cities had the lowest level. The collaborative level of non-resource-based cities was higher than that of resource-based cities. ② The gap in the collaborative level of carbon reduction， pollution reduction， and green expansion in different regions widened， and the polarization of the entire basin was gradually increasing. The coordinated promotion of carbon reduction， pollution reduction， and green expansion in the Yellow River Basin still faces significant structural and fundamental pressures， and the problem of uneven development between regions is more prominent. ③ The urbanization rate and the proportion of the tertiary industry were the core driving factors for the coordinated development of carbon reduction， pollution reduction， and green expansion in the Yellow River Basin， while per capita GDP， the proportion of the secondary industry， and the level of science and technology were auxiliary influencing factors. The article studies and deconstructs the level， dynamic evolution trend， and influencing factors of coordinated development of carbon reduction， pollution reduction， and green expansion in the Yellow River Basin， providing policy basis for ecological protection and high-quality development in the Yellow River Basin.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6025-6037"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012950","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":"[Social-ecological System Risk Assessment and Management Zoning in the Beijing-Tianjin-Hebei Region from a Spatio-temporal Dynamic Relationship Perspective].","authors":"Lu Zuo, Jun-Jing Lu, Lei-Gang Sun, Qing-Tao Hao, Qin-Yi Wang, Peng-Fei Zhang, Xiao-Qian Ma","doi":"10.13227/j.hjkx.202508085","DOIUrl":"https://doi.org/10.13227/j.hjkx.202508085","url":null,"abstract":"&lt;p&gt;&lt;p&gt;The interaction of multiple risk factors between natural systems and human societies during rapid urbanization poses significant ecological risk to regions. Scientifically assessing and managing these risks is crucial for regional ecological security and sustainable development. This study adopts a multi-source risk spatio-temporal dynamic relationship perspective， incorporating the social-ecological system （SES） framework to assess and analyze the spatio-temporal evolution characteristics of ecosystem risk， social system risk， and comprehensive ecological risk in the Beijing-Tianjin-Hebei （BTH） Region from 2000 to 2020. Based on the spatio-temporal dynamic correlations among different risk types， the study area is categorized into six sub-regions and three macro-regions using bivariate spatial autocorrelation and hot spot-cold spot analysis. Furthermore， optimal parameters-based Geodetector analysis is employed to investigate the driving differences of comprehensive ecological risks across the entire region and within each partitioned zone. The results show that： ① The mean values of ecosystem risk， social system risk， and comprehensive ecological risk in the BTH Region were 0.464， 0.299， and 0.381， respectively. Their distribution exhibited a spatial pattern of low values in the northwest and high values in the southeast. The risk levels of various types along the Yanshan-Taihang Mountains were relatively low， and the risk in plain areas was significantly higher than that in mountainous areas， with ecosystem risk being stronger than social system risk. ② Over the past 20 years， ecosystem risk decreased by 2.55% and social system risk increased by 2.01%， resulting in a slight decrease （0.78%） in comprehensive ecological risk. Comprehensive ecological risk decreased significantly in the northwestern mountainous areas and the coastal wetlands in the eastern plains. Urbanized areas exhibited a ring structure： constant risk levels in the core and increased risk in the peripheral zones. ③ A significant and strengthening positive spatial correlation existed between ecosystem risk and social system risk. The proportions of areas with significantly increased and decreased comprehensive ecological risks were 18.63% and 19.06%， respectively. Emergency control macro-zones were concentrated in urban expansion fringes， key control macro-zones were located within urban core areas， and close monitoring macro-zones were distributed in the urban periphery and coastal belts. Dynamic regulation macro-zones covered the most extensive area， while preventive management macro-zones and conservation macro-zones were primarily situated within the Yanshan-Taihang Mountains Ecological Functional Area. ④Topography， urban construction， and socio-economic activities dominated the spatial differentiation of comprehensive ecological risk across the entire region and within monitoring macro-zones. Urban construction exerted a particularly prominent influence within contro","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6392-6404"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012973","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-temporal Characteristics Evolution of Land Use Carbon Emissions in China from 2000 to 2021 and Carbon Emission Prediction].","authors":"Jia-Wei Yu, Zu-Heng Cheng, De-Xing An, Wen-Lin Zhang, Yu-Fen Niu, Jun Tong","doi":"10.13227/j.hjkx.202501138","DOIUrl":"https://doi.org/10.13227/j.hjkx.202501138","url":null,"abstract":"&lt;p&gt;&lt;p&gt;The spatiotemporal evolution of carbon emissions and its future trend prediction， as an important scientific issue in response to global climate change， has become a key area of research in climate science， environmental science， and policy studies. As the world's largest emitter of carbon， China's land use changes have had a profound impact on the dynamic changes in carbon emissions. This study utilizes the annual land use dataset from Wuhan University， socioeconomic data from the China Statistical Yearbook， and MODIS global net primary productivity （NPP） data to examine the carbon emissions and carbon sequestration from various 3land types such as urban areas， arable land， and forest land in different regions. It systematically analyzes the specific impact of land use changes in China on carbon emissions from 2000 to 2021. Additionally， the study employs a Gaussian Process Regression （GPR） model for carbon emission forecasting and analyzes the spatial distribution of carbon emissions in relation to economic development using the Gini coefficient and the TAPIO decoupling model. The results indicate that： ① From 2000 to 2021， construction land expanded by 67.28% （2000-2021）， with an average annual growth rate exceeding 4%. Significant conversion of arable land occurred in the eastern region. Forest land/water body areas increased by 2.12% and 10.38%， respectively， with notable ecological restoration in the western region. Grassland， arable land， and unused land decreased by 1.86%-3.28%， showing clear characteristics of intensive land use. ② From 2000 to 2021， carbon emissions from construction land dominated in proportion， with total emissions increasing by 235% （an annual growth rate of 6.07%） and spatial diffusion extending to the central and western regions. Forest carbon sequestration increased by 16.6% （an annual growth rate of 0.77%）， while carbon absorption by grasslands slightly declined， and the carbon function differentiation between the eastern and western regions intensified. ③ The carbon emission Gini coefficient decreased from 0.592 2 in 2000 to 0.540 7 in 2021， indicating a more even distribution of carbon emissions. The carbon emissions of the top 10% grids increased from 108.9 million tons to 330.4 million tons， showing that high-emission areas were still driving the growth of carbon emissions. The internal differences in the western region were the largest （Gini coefficient of 0.847 3）. ④ From 2000 to 2013， China was in a \"weak decoupling\" state， with economic growth accompanied by an increase in carbon emissions. From 2014 to 2016， China entered a \"strong decoupling\" phase， where GDP growth occurred alongside a reduction in carbon emissions. From 2017 onwards， carbon emissions began to rise again， returning to a \"weak decoupling\" state. ⑤ The GPR model predicted that China's carbon emissions will peak in 2028， and carbon neutrality will be achieved before 2060. The western region has already become a carbon sink， while th","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"5907-5924"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012365","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":"[Effects of Biochar Amendment on Microbial Community Structure in Purple Soils with Varying Acidification Levels].","authors":"Lu Peng, Yu-Xi Guo, Jie Lu, Meng Chen, Juan Huang, Liu-Yan Zhou, Zi-Fang Wang, Wen-Cai Dai, Ming Gao","doi":"10.13227/j.hjkx.202506317","DOIUrl":"https://doi.org/10.13227/j.hjkx.202506317","url":null,"abstract":"<p><p>Biochar， as a soil amendment， plays an important role in increasing soil pH and promoting microbial diversity. An indoor incubation experiment combined with high-throughput sequencing was conducted to investigate the effects of biochar addition on soil pH， organic matter content， and microbial community structure in purple soils with different acidification degrees， aiming to elucidate the response characteristics of purple soils to biochar input under varying acidification conditions and to provide a theoretical basis for improving soil fertility and promoting sustainable utilization of purple soils. Biochar was added at 3% of the dry soil weight and incubated for 63 days under laboratory conditions. The treatments included three acidification levels： T1， severe acidification （pH=4.48）； T2， moderate acidification （pH=4.90）； and T3， slight acidification （pH=5.82）. The results showed that： ① Under equal biochar application， compared with pre-incubation values， soil pH increased significantly in all treatments by 0.09， 0.34， and 0.37 units for T1， T2， and T3， respectively （<i>P</i><0.05）. Organic matter increased by 70.13%-118.98%， with the highest increase observed in moderately acidified soil. ② Microbial community structures differed markedly among the three acidification levels， and greater acidification reduced microbial richness. Both bacterial richness （Chao1） and diversity （Shannon） followed the order T3>T2>T1； fungal richness （Chao1） followed T3>T2>T1， while fungal diversity （Shannon） followed T3>T1>T2. ③ The dominant bacterial phyla in all treatments were Proteobacteria and Chloroflexi， while the dominant fungal phyla were Ascomycota， Basidiomycota， and Mortierellomycota. ④ Biochar addition altered microbial community structures across different acidification levels， with dominant microbial taxa shifting along the soil pH gradient and more complex and stable co-occurrence networks forming under near-neutral conditions. ⑤ Redundancy analysis revealed that pH， TN， AP， C/N， and <i>β</i>-glucosidase were the main factors shaping bacterial community structure， whereas TN， C/N， cellobiohydrolase， and sucrase were the main factors influencing fungal community structure. In conclusion， biochar application improved soil pH， organic matter， and total nitrogen contents； altered microbial community succession and network characteristics； and thereby enhanced soil ecological health.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 9","pages":"6504-6515"},"PeriodicalIF":0.0,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149012863","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}