环境科学最新文献

{"title":"[Characteristics and Sources of VOCs Pollution in Typical Regions of Tianjin].","authors":"Jing-Yun Gao, Shi-Yuan Feng, Yu Bai, Guang-Xun Liu, Zhe Li, Zhi-Mei Xiao, Hong Xu, Jian-Hui Wu, Ning Yang","doi":"10.13227/j.hjkx.202502103","DOIUrl":"https://doi.org/10.13227/j.hjkx.202502103","url":null,"abstract":"<p><p>The characterization and source apportionment of atmospheric volatile organic compounds (VOCs) were investigated based on high-resolution online monitoring data observed from April to September in 2024 at typical sites in Tianjin of the Central Urban Area and Binhai New Area. The results showed that the average concentrations of VOCs in different areas were ranked as follows: Central Urban Area (32.95 μg·m<sup>-3</sup>) < Nanjiang Port (53.49 μg·m<sup>-3</sup>) < Lingang Industrial Zone (61.16 μg·m<sup>-3</sup>) < Binhai Development Zone (62.18 μg·m<sup>-3</sup>). The chemical compositions of VOCs were alkanes, aromatics, alkenes, and alkynes, accounting for 62.46%-71.45%, 19.39%-25.87%, 6.35%-14.48%, and 0.69%-3.67% of VOCs concentration on average, respectively. Higher alkane proportions were observed in Nanjiang Port and Binhai Development Zone, while the highest proportions of alkenes and aromatics were observed in the Central Urban Area and Lingang Industrial Zone, respectively. The ozone formation potential (OFP) values were ranked as follows: Central Urban Area (98.81 μg·m<sup>-3</sup>) < Nanjiang Port (132.46 μg·m<sup>-3</sup>) < Binhai Development Zone (154.36 μg·m<sup>-3</sup>) < Lingang Industrial Zone (179.18 μg·m<sup>-3</sup>). Aromatics and alkenes were the main contributors to OFP, accounting for 30.73%-51.48% and 25.61%-48.32%, respectively. Aromatics had the highest contribution to OFP in Binhai Development Zone, Lingang Industrial Zone, and Nanjiang Port, while alkenes had the highest contribution to OFP in the Central Urban Area. The ratio of <i>m</i>/<i>p</i>-xylene to ethylbenzene indicated that VOCs were mainly emitted locally in the Central Urban Area, Binhai Development Zone, and Lingang Industrial Zone, while the long-distance transmission of VOCs had a certain impact on Nanjiang Port. Positive matrix factorization was applied to estimate VOCs source contributions, and the results showed that the sources of VOCs were significantly different in different regions. Gasoline vehicles, LPG volatilization, petrochemical industry emissions, NG volatilization, solvent usage, natural sources, and combustion were identified as major sources of VOCs in the Central Urban Area, accounting for 24.5%, 19.4%, 13.9%, 13.1%, 11.8%, 9.5%, and 7.8%, respectively. While in Binhai New Area, the main sources of VOCs contributions were diesel mobile sources, LPG volatilization, gasoline vehicles, solvent usage, food processing, petrochemical industry emissions, and combustion, with the contributions of three regions being 17.8%-37.3%, 17.2%-22.1%, 14.5%-18.8%, 6.4%-21.7%, 5.7%-23.3%, 6.9%-7.8%, and 2.8%-9.2%, respectively. Future attention should focus on gasoline vehicles, LPG volatilization, NG volatilization, and solvent usage in the Central Urban Area, while diesel mobile sources, LPG volatilization, gasoline vehicles, solvent usage, food processing, and petrochemical industry emissions were the key prevention and con","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1379-1388"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460232","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":"[Soil Functional Genes of Carbon, Nitrogen, Phosphorus, and Sulfur Cycle at Different Restoration Stages of <i>Ulmus pumila</i> in Pingshuo Mining Area].","authors":"Hui Ma, Shuang Liu, Jun-Jian Li, Hong Zhang, Yong Liu, Zi-Qiang Du","doi":"10.13227/j.hjkx.202501261","DOIUrl":"https://doi.org/10.13227/j.hjkx.202501261","url":null,"abstract":"<p><p>Open-pit coal mining has caused serious damage to the ecological environment, and vegetation restoration is a major management for ecological restoration in mining areas. The nutrient cycling mediated by soil microorganisms is closely related to the soil functional genes. Studying the effects of long-term vegetation restoration on soil carbon, nitrogen, phosphorus, and sulfur functional genes is of great significance for ecological restoration in mining areas. The reclamation of <i>Ulmus pumila</i> (UP) forest land in the Pingshuo open-pit coal mine was selected as the research object. Rhizosphere soil samples of UP with growth years of 5 a (UP5), 15 a (UP15), and 25 a (UP25) were collected to analyze the relationship between soil chemical properties and the abundance of carbon, nitrogen, phosphorus, and sulfur functional genes. The results showed that with the increase in restoration time, the nutrient content of the soil significantly increased (<i>P</i> &lt; 0.05). The total abundance of functional genes related to the carbon, nitrogen, phosphorus, and sulfur cycles increased, and the nitrogen cycle was the main biochemical process in UP forest land. Among all carbon fixation genes, the <i>acsA</i> involved in the reducing acetyl CoA pathway had the highest abundance. The main biochemical process of the phosphorus cycle was organic phosphorus mineralization, and the sulfur oxidation process was stronger than the sulfur reduction process. When the growth period was 25 a, the diversity and stability of microbial functional genes were highest. Additionally, mutual promotion and cooperation among genes were the main mode of function genes activity. In the UP forest land, total carbon and available phosphorus were the primary factors for carbon cycling genes, while total carbon, total nitrogen, nitrate nitrogen, and available phosphorus were the primary factors for nitrogen cycling genes. The sulfur cycling genes were significantly positively correlated with soil chemical properties (<i>P</i> &lt; 0.01). The results showed that the soil chemical properties, carbon, nitrogen, phosphorus, and sulfur functional genes diversity and stability in 25 a of UP were significantly higher than those in 5 a and 15 a, and soil quality has been improved. In a word, with the restoration time increasing, vegetation restoration impacted the abundance and diversity of functional genes by altering the soil chemical properties, ultimately promoting the restoration and stability of the ecosystem. These results are helpful to understand the influence of carbon, nitrogen, phosphorus, and sulfur-related functional genes in the process of vegetation restoration and to provide genetic scientific basis for ecological restoration in the mining areas.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1966-1974"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460291","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 Dynamics of Land Use and Carbon Stocks Under Multiple Scenarios in the Yangtze River Basin].","authors":"Wen-Fei Kuang, Yong-Chao Liu, Jia-Lin Li, Chao Ying, Luo-Dan Cao, Jie Zhong","doi":"10.13227/j.hjkx.202502020","DOIUrl":"https://doi.org/10.13227/j.hjkx.202502020","url":null,"abstract":"<p><p>China's Yangtze River Basin holds significant ecological and economic importance. Understanding land use dynamics and carbon stock changes in this region is critical for promoting sustainable development. This study examines the spatiotemporal evolution of land use and carbon stocks from 1985 to 2022 by integrating the FLUS and InVEST models. It further projects changes through 2050 under three scenarios：inertial development，ecological protection，and economic development. The results reveal that：① Land use changes demonstrated a dynamic interplay of cultivated land decline（-26.5%），ecological restoration（forest 11.2%，wetland 14 681 km²），and rapid urban expansion（impervious surfaces ×4.08）. ② Net carbon stock increased by 1.83×10⁹ t during 1985-2022，with marked temporal variability. Significant declines occurred in cropland（-16.8%）and forest（-11.6%）carbon stocks between 1995 and 2000，while recent gains were observed in woodland（30.7%）and grassland（6.3%）from 2020 to 2022. ③ Land use transitions played a pivotal role in carbon dynamics：Conversion from cropland to forest contributed 1.26×10⁹ t of carbon gain（42.7% of total），whereas urbanization-driven cropland loss led to a 3.98 × 10⁸ t decrease. Wetland restoration and woodland expansion contributed an additional 2.01×10⁸ t and 5.29×10⁹ t，respectively. ④ Scenario analysis indicated that ecological protection yielded the highest carbon accumulation（72.47×10⁸ t）through wetland（118.9%）and forest（8.3%）expansion. In contrast，inertial and economic development scenarios resulted in 9.1% and 5.8% reductions due to increased impervious surface area. Spatial analysis identified the Yangtze River Delta and the Chengdu-Chongqing urban clusters as major carbon loss hotspots. The findings underscore the importance of implementing ecological protection strategies，including stricter controls on agricultural land conversion and enhanced wetland and forest restoration，to bolster regional carbon sinks and support China's dual carbon goals.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1914-1927"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460403","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":"[Estimation of Synergistic Carbon Emission Reduction Potential in the Construction of \"Zero-waste City\" in Yantai].","authors":"Zhi-Hui Su, Mu-Jie Wang, Ping Li, Zhi-Yuan Ren, Chun-Feng Duan, Zheng Zhang","doi":"10.13227/j.hjkx.202501092","DOIUrl":"https://doi.org/10.13227/j.hjkx.202501092","url":null,"abstract":"<p><p>The construction of a \"zero-waste city\" is synergistic with carbon emission reduction. Estimating the carbon emission reduction potential of various solid wastes during the \"zero-waste city\" construction process, which is achieved through source reduction, harmless disposal, and resource utilization, can provide a scientific foundation for formulating and implementing relevant solid waste management measures to obtain greater carbon emission reduction benefits. Taking Yantai City as an example, based on the improved WARM model, the emission factor method was used to predict the carbon emission reduction potential throughout the entire life cycle of solid wastes from the industrial sector, urban and rural living areas, and agricultural sector. The results showed that through the construction of a \"zero-waste city, \" Yantai City was expected to achieve a carbon emission reduction benefit of 19.52 million tons (calculated in CO₂eq, hereinafter the same) in the field of solid waste. In the industrial sector, although the total amount of solid waste generated increased, a carbon emission reduction benefit of 17.45 million tons could still be realized. This would be accomplished through source reduction of solid waste in the coal-fired power industry, such as fly ash, and by increasing the utilization rate of gold tailings in building materials production. In the urban and rural living areas, the realization of 100% incineration treatment of domestic waste will decrease the amount of landfill and, at the same time, reduce carbon emissions. In the agricultural sector, by changing the utilization method of straws from crushing and returning to the field to fuel utilization, a carbon emission reduction of approximately 2 million tons could be generated. Increasing the intensity of carbon emissions source reduction in the coal-fired power industry, strengthening the research and development of resource utilization technologies for gold tailings, and improving the level of large-scale fuel utilization of straws are important approaches for the coordinated carbon emission reduction in the construction of a \"zero-waste city\" in Yantai City.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1623-1633"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460444","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 Temporal and Spatial Dynamic Changes in Vegetation Coverage and Driving Factors in the Bosten Lake Basin Based on the NDVI Index].","authors":"Meng-Jing Guo, Shao-Shun Han, Bo Yuan, Wen Wang, Ke Xiang, Jiao Zhang, Hui-Yi-Zhe Zhao","doi":"10.13227/j.hjkx.202501203","DOIUrl":"https://doi.org/10.13227/j.hjkx.202501203","url":null,"abstract":"<p><p>The Bosten Lake, as an ecological key hub in the arid region of Northwest China, has a relatively unique ecological environment, making it challenging to maintain ecological balance. Studying the dynamic changes of the normalized difference vegetation index (NDVI) in the Bosten Lake Basin and its driving factors is of great significance for maintaining the stability and sustainable development of the basin's ecosystem. Based on Landsat data from 2001 to 2023, the NDVI values of the Bosten Lake Basin were calculated. The Mann-Kendall trend significance test, Sen's slope estimation method, and Hurst index were used to analyze the spatiotemporal dynamic changes of NDVI in the Bosten Lake Basin, and the relationship between climatic factors and NDVI was explored. The results showed that: ① The annual maximum NDVI in the Bosten Lake Basin generally showed an increasing trend, with a growth rate of 0.003 3 a^-1. The spatial distribution characteristics of NDVI were relatively obvious, mainly dominated by high vegetation coverage, with 52.18% of the area showing an increasing trend. ② Seasonally, the NDVI during the growing season showed an increasing trend, with the highest NDVI in summer and the lowest in spring, and the trend of summer NDVI changes was consistent with the annual maximum NDVI changes. ③ The Hurst index predicted that 34.72% of the area in the Bosten Lake Basin would show a degradation trend in NDVI, while 65.28% would show an improvement trend. ④ The annual maximum NDVI in the Bosten Lake Basin from 2001 to 2020 was positively correlated with rainfall, temperature, sunshine hours, and evaporation and significantly correlated with sunshine hours and total evaporation, with correlation coefficients of 0.374 and 0.494, respectively. Therefore, the NDVI in the Bosten Lake Basin has shown an improving trend over the past 23 years, positively correlated with climatic factors. This study provides a scientific basis for the ecological environment construction, ecosystem management, and ecological balance maintenance in the Bosten Lake Basin.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1767-1779"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460239","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":"[Carbon Reduction Effect of Promoting New Energy Vehicles in China: Cross Regional Power Transmission Perspective].","authors":"Yuan-Chun Zhou, Neng Tian, Run-Han Zhang, Dong-Qin Tian, Yu-Qing Shi","doi":"10.13227/j.hjkx.202501013","DOIUrl":"https://doi.org/10.13227/j.hjkx.202501013","url":null,"abstract":"<p><p>Vigorously promoting new energy vehicles is an important measure for China's transportation industry to implement the \"dual carbon\" strategy. In order to comprehensively understand the carbon emission transfer and carbon reduction effect caused by cross regional consumption of electricity in the promotion of new energy vehicles, a refined provincial new energy vehicle dataset was first constructed, and the electricity demand during the use stage of new energy vehicles in various provinces of China was calculated. Subsequently, based on the quasi-input-output model, an interprovincial power transmission network was constructed, and the carbon emission transfer amount and transfer path caused by the use of new energy vehicles in 2020 and 2021 were calculated. Finally, the carbon reduction effect of promoting new energy vehicles in various provinces of China was evaluated through counterfactual scenario simulations. The results showed that the promotion of new energy vehicles has intensified the trend of carbon emission transfer from economically developed coastal areas to underdeveloped central and western regions, and the phenomenon of carbon emission transfer within each region was also quite evident. Carbon emissions will also be indirectly transferred through power hubs. From a national perspective, new energy vehicles had significant emission reduction benefits compared to fuel vehicles and were closely related to the power structure of local and power output regions. Provinces with a high proportion of clean energy use had more prominent emission reduction effects.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1566-1575"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460263","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 Temporal and Spatial Evolution Characteristics and Driving Factors of Ecological Environment Quality in Beibu Gulf Port Area].","authors":"Yu-Xiao Feng, Wen He, Jin-Ye Wang, Dan Liu, Yue-Feng Yao","doi":"10.13227/j.hjkx.202501054","DOIUrl":"https://doi.org/10.13227/j.hjkx.202501054","url":null,"abstract":"<p><p>The evaluation of ecological environment quality and the analysis of the causes of ecological change are important aspects of regional ecological management. In this study, based on the factors of greenness (NDVI), humidity (WET), heat (LST), and dryness (NDBSI), the salinity index (SI) was introduced to build an improved ecological remote sensing index (MRSEI). The spatial and temporal distribution pattern and driving mechanism of eco-environmental quality in the Beibu Gulf port area from 2000 to 2024 were analyzed. The results showed as follows: ① From 2000 to 2024, the overall ecological environment quality in the study area showed a slow improvement trend, and the MRSEI grade was mainly in the middle level, with the average annual value ranging from 0.25 to 0.68, showing a spatial distribution pattern of high in the west and low in the east. ② There was a strong spatial autocorrelation of ecological environment quality in the study area. The spatial aggregation patterns were mainly H-H and L-L. The H-H gathering area was mainly forest land and mountain, and the L-L gathering area was mainly agricultural land and construction land. ③ In 2000-2024, the area of ecological environment quality improvement was significantly larger than the area of degradation, and the area of no significant improvement and significant degradation was the most extensive. The future change trend is mainly future degradation. ④ The ecological environment quality in the study area was influenced by both natural and human factors. Among them, the average annual temperature had the strongest explanatory power, followed by evapotranspiration, slope, distance to artificial surface, and NPP. The interaction of all factors increased to a certain extent, and the interaction effect of average annual temperature and evapotranspiration was the strongest.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1805-1818"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460267","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 Distribution Prediction and Influencing Factors of Soil Surface pH Based on Interpretable Ensemble Machine Learning].","authors":"Li Wang, Hou-Bao Fan, Yan-Wei Zhang, Yong-Zhong Tan","doi":"10.13227/j.hjkx.202501047","DOIUrl":"https://doi.org/10.13227/j.hjkx.202501047","url":null,"abstract":"<p><p>Accurately quantifying the spatial distribution of topsoil pH and identifying its influencing factors is essential for recognizing potential land-use challenges and promoting the recovery and balance of soil ecological functions. In this study, 1 795 soil samples were collected from the hilly region of southern Sichuan, China, to model and analyze topsoil pH using four base machine learning models: random forest (RF), support vector regression (SVR), extreme gradient boosting (XGB), and neural network (ANN), as well as two ensemble learning approaches: Boosting and Stacking. Model performance was assessed and compared, and Shapley additive explanations (SHAP) were applied to interpret the contribution and interaction of environmental predictors. The results showed that ensemble models achieved higher predictive accuracy than individual base learners, with the Boosting model yielding the best performance (<i>R</i>²=0.862). All six models demonstrated consistent spatial prediction trends, though a slight compression in value range was observed between predicted and measured pH values. Soil pH across the study area displayed a spatially stratified pattern, generally decreasing from north to south. The four most influential factors were TK, BD, SOC, and annual precipitation. Partial dependence analysis indicated that soil pH increased significantly when TK ranged from 16.25 to 17.34 g·kg^-1 but decreased once TK exceeded 17.83 g·kg^-1. SOC exhibited a negative effect on soil pH, particularly when SOC content was greater than 8.25 g·kg^-1. Moreover, interaction analysis revealed heterogeneity in the synergistic effects among various factors. These findings highlight the potential of interpretable ensemble learning methods for modeling soil properties and provide theoretical support for developing targeted strategies to regulate soil pH. They also offer a scientific basis for improving soil health resilience and advancing sustainable soil ecological management in complex agricultural landscapes.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1941-1953"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460354","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":"[Coupling Effect of Digitization and Greening and Its Impact Mechanism on New Quality Productivity].","authors":"Yan Liu, Jun-Song Jia, Yu-Fei Zhong","doi":"10.13227/j.hjkx.202502156","DOIUrl":"https://doi.org/10.13227/j.hjkx.202502156","url":null,"abstract":"<p><p>Digitization and greening are the preferred paths for the current development of new quality productivity. Accordingly, by constructing indicators of digitization, greening, and new quality productivity, we analyze the coordination degree of digitization and greening coupling and its promotion mechanism for the improvement of new productivity in 30 provinces in China from 2012-2022 by using the modified coupling, benchmark regression, mediating effect, moderating effect, and threshold effect models. The results showed that: First, the overall coupling coordination of digitization and greening was not high, but it was gradually increasing, and there was an obvious clustering effect, with \"Beijing-Shanghai-Guangdong\" dominating in the east, \"Hubei\" dominating in the center, and \"Sichuan-Chongqing\" dominating in the west, manifesting itself in the form of an \"eastern leading, central lagging, rise of the west\" pattern. Second, in promoting the development of new quality productivity, the coupling effect of digitization and greening showed a significant positive contribution in different regions, with the most significant contribution in the eastern region, followed by that in the central region, and relatively weaker in the western region. Further mechanism analysis revealed that science and technology innovation played an important intermediary role in promoting the development of new productivity through the coupling effect of digitization and greening, which was further enhanced by the increase in the level of industrial agglomeration. In addition, the impact of environmental regulation on the coupling effect of digitization and greening showed an inverted \"U\" shape, and excessive environmental regulation may weaken its effect on the promotion of new productivity.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1474-1485"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460386","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":"[Synergistic Impact of Climate Change and Human Activities on Vegetation Coverage in the Economic Belt on the Northern Slope of the Tianshan Mountains].","authors":"Ya-Shu Lü, Han Yang, Maimaitiaili Kamuran, Jia-Hui Dai","doi":"10.13227/j.hjkx.202502071","DOIUrl":"https://doi.org/10.13227/j.hjkx.202502071","url":null,"abstract":"<p><p>Based on long-term vegetation index and meteorological data from 2000 to 2022, this study analyzes the spatiotemporal changes in fractional vegetation coverage (FVC) in the economic belt on the northern slope of Tianshan Mountains and quantifies the impacts of climate change and human activities. Trend analysis, the Hurst index, the geographical detector method, and residual analysis are used to assess FVC variation and predict future trends. The results showed that: ① From 2000 to 2022, the FVC of the northern Tianshan economic belt exhibited a slow fluctuating upward trend, with an average annual growth rate of 1.2×10^-3 a^-1. The spatial distribution was heterogeneous, presenting a \"high in the northwest-southeast axis and low around the edges\" pattern, with low fractional vegetation coverage (FVC ≤ 0.2) being dominant, accounting for 62.45%. ② During the same period, both improvement and degradation trends coexisted, and the Hurst index analysis indicated that 51.87% of the region may face potential risks of vegetation degradation in the future. ③ The geographical detector analysis showed that land use was the most significant driving factor for FVC variation, with a q-value of 0.670, making land use one of the key factors influencing FVC change. ④ The relative contribution rates of climate change and human activities to the variation in fractional vegetation coverage were 15.54% and 84.46%, respectively. In conclusion, future ecological construction should focus on strengthening the role of human activities in promoting the increase of fractional vegetation coverage, while enhancing the monitoring and protection of existing vegetation to prevent degradation trends.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"47 3","pages":"1754-1766"},"PeriodicalIF":0.0,"publicationDate":"2026-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147460399","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}