Environmental Earth Sciences最新文献

{"title":"Physical triggering mechanism of carbonatic saprolitization in the Central Yunnan, China","authors":"Chenxi Wang,&nbsp;Jiaming Zhang,&nbsp;Zemin Xu,&nbsp;Lin Tian,&nbsp;Guie Shi","doi":"10.1007/s12665-025-12460-5","DOIUrl":"10.1007/s12665-025-12460-5","url":null,"abstract":"<div><p>This study systematically investigates the physical saprolitization mechanism of carbonate rocks in central Yunnan, China. Physical weathering plays a dominant role, at least during the early to middle stages of saprolitization, based on comparative analyses of saprolite samples with varying weathering (powderization) degrees in terms of crystal morphology, chemical composition, and pore structure. Scanning electron microscopy and pore structure analysis reveal that the structural connections between crystal grains are progressively destroyed during the transformation from corestone to saprolite, a process highly consistent with fatigue failure characteristics. Following matrix suction experiments confirming that moisture fluctuations regularly alter suction within rocks, a theoretical analysis was introduced to further explore the triggering mechanism. Inspired by the one-dimensional spherical soil particle model, it is inferred that suction fluctuations accumulate at the grain scale to generate dynamic tensile stresses, providing a plausible source of dynamic loading responsible for fatigue failure. Field evidence further supports this mechanism: Saprolite tends to form near the bedrock–soil interface, as the soil helps maintain a variable-humidity condition around the bedrock. In the same region, saprolites near the surface exhibit a higher degree of powderization than those at depth, and greater powderization also occurs in areas with higher pore connectivity—both consistent with more active moisture migration. This study establishes a closed-loop mechanism linking variable humidity, moisture migration, dynamic loading, and structural degradation, and offers a new perspective on saprolitization beyond the traditional framework of chemical weathering.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144814436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land-use/land-cover change and its impact on ecosystem carbon storage in Binhai New Area, Tianjin, China from 1985 to 2060","authors":"Min Song,&nbsp;Shuling Yu,&nbsp;Huawei Qin,&nbsp;Maihemutijiang Mijiti,&nbsp;Haitao Wang","doi":"10.1007/s12665-025-12498-5","DOIUrl":"10.1007/s12665-025-12498-5","url":null,"abstract":"<div><p>The transformation of Land-Use/Land-Cover Change (LULC) plays a pivotal role in shaping ecosystem carbon storage, yet quantitative assessments of its effects and future trends remain limited. Given China’s targets of reaching carbon peak by 2030 and carbon neutrality by 2060, understanding these dynamics is crucial. This study focuses on the Binhai New Area of Tianjin, China, using remote-sensing imagery to analyze LULC data from 1985 to 2020. We forecasted land use patterns for 2030 and 2060 across three scenarios: baseline trend scenario (BTS), priority ecological scenario (PES), and priority urbanization scenario (PUS), employing the Patch-generated Land Use Simulation (PLUS) model. Changes in ecosystem carbon storage were evaluated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. A net reduction of 1.31 Tg C was observed in ecosystem carbon storage over the 35-year period (1985–2020), mainly because of the transformation of all land types into built-up land, led predominantly by dry farmland conversion. By 2030, ecosystem carbon storage decreased by 0.94 Tg C under the BTS and 2.15 Tg C under the PUS, but increased by 0.11 Tg C under the PES. By 2060, reductions were 0.96 Tg C (BTS) and 3.15 Tg C (PUS), while the PES showed only a 0.29 Tg C decline. These results emphasize the importance of ecological conservation in reducing declines in ecosystem carbon storage. Therefore, under China’s dual-carbon targets, the PES should be prioritized in future land-use planning to enhance carbon sequestration and support sustainability goals.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144814286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydraulic conductivity of compressible clayey soil stabilized with kraft black liquor and composite cement","authors":"Bruno Pereira de Queiroz,&nbsp;Rejane Nascentes,&nbsp;Roberto Lopes Ferraz,&nbsp;Maria Eugenia Gimenez Boscov,&nbsp;Mauricio Paulo Ferreira Fontes","doi":"10.1007/s12665-025-12471-2","DOIUrl":"10.1007/s12665-025-12471-2","url":null,"abstract":"<div><p>This study examined the hydraulic behavior and geochemical interactions of a compacted high-plasticity clayey soil (CH) and its mixtures with kraft black liquor (KBL) and composite cements CP II˗E˗32 and CP II˗F˗32 for landfill liner applications. Mixtures with 3% and 5% black liquor (by dry soil mass) were tested for hydraulic conductivity and chemical stability. Specimens were statically compacted in PVC molds (10 cm in diameter, 12 cm in height) at optimum water content and dry unit weight, based on standard Proctor tests. Percolation tests were conducted at 20°C under a hydraulic gradient of 15, with leachate analyzed for pH and cation concentrations via atomic absorption spectrophotometry. Cation exchange capacity (CEC) was also determined. Black liquor reduced the optimum moisture content and increased the maximum dry density, promoting clay dispersion and lowering hydraulic conductivity by up to 10 times. Mixtures with 3% black liquor and 5% liquor-cement CP II˗F˗32 achieved the lowest hydraulic conductivity (2.4–3.4 × 10^–10 m/s). In contrast, mixtures with CP II˗E˗32 exhibited higher and more variable conductivity, likely due to increased Ca²⁺ leaching, which induced particle flocculation. Black liquor addition increased pH and Na⁺ concentration, enhancing CEC. Cement CP II˗F˗32 further intensified these effects, increasing Al³⁺ concentrations without impairing clay dispersion. A strong correlation was found between the <span>([text{Na}]/[text{Ca}])</span> ratio and hydraulic performance, with higher values associated with lower hydraulic conductivity. These results highlight the potential of soil-liquor-cement mixtures, particularly those with CP II˗F˗32, for landfill liners due to improved hydraulic conductivity and chemical stability.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144814313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of particulate matter pollution using a long short-term memory model in Zhejiang Province, China","authors":"Ahmad Hasnain,&nbsp;Ayesha Sohail,&nbsp;Uzair Aslam Bhatti,&nbsp;Geng Wei,&nbsp;Waseem ur Rahman,&nbsp;Waqas Akram Cheema,&nbsp;Muhammad Asif,&nbsp;Muhammad Azam Zia","doi":"10.1007/s12665-025-12463-2","DOIUrl":"10.1007/s12665-025-12463-2","url":null,"abstract":"<div><p>Air pollution, one of the most serious environmental issues that people face, affects the standard of living in urban areas. Strategies for assessing and alerting the public to anticipated hazardous levels of air pollution can be developed using particulate matter (PM) forecasting models. Accurate assessments of pollutant concentrations and forecasts are essential components of air quality evaluations and serve as the foundation for making informed strategic decisions. In the current study, the Long Short-Term Memory (LSTM) model, a deep learning approach, was employed to forecast PM pollution along with meteorological variables in Zhejiang Province, China. The model’s performance was assessed using the cross-validation (CV), mean absolute error (MAE), root mean squared error (RMSE), and the coefficient of determination (R²). According to our findings, the model performed well in predicting PM₁₀ (R² = 0.76, RMSE = 11.51 µg/m³, and MAE = 8.74 µg/m³) and PM_2.5 (R² = 0.74, RMSE = 7.06 µg/m³, and MAE = 5.41 µg/m³) concentrations. Moreover, there was a downward trend in PM concentrations from 2019 to 2022, but Zhejiang Province experienced an increase in PM levels in 2023. These results are reliable and underscore the need for increased efforts to reduce air pollution in the future.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive models for earthquake-induced landslides: machine learning based on real case histories","authors":"Hao Bai,&nbsp;Fei Wang,&nbsp;Wei Wang,&nbsp;Wubin Wang","doi":"10.1007/s12665-025-12490-z","DOIUrl":"10.1007/s12665-025-12490-z","url":null,"abstract":"<div><p>In this study, the deformation of earth slopes under earthquakes was evaluated using machine learning techniques. While traditional empirical models have been widely used to estimate seismic slope deformations, they often suffer from limited accuracy and generalizability due to their reliance on simplified assumptions and region-specific datasets. To address this gap, extensive real case histories on seismic deformations of earth slopes during earthquakes in different regions across the world were gathered and examined. Most important factors affecting earthquake-induced deformations of the slopes were characterized. Five models were then developed for prediction of seismic deformation of earth slopes (<i>D</i>) using extreme learning machine (ELM), random forest (RF), genetic programming (GP), support vector regression (SVR), and hybrid whale optimization algorithm (WOA)-SVR. Subsequently, the accuracy of developed models was measured. The results indicated that WOA-SVR model (<i>R</i>^<i>2</i> = 0.821, RMSE = 0.819) has higher accuracy than SVR (<i>R</i>^<i>2</i> = 0.780, RMSE = 0.852), GP (<i>R</i>^<i>2</i> = 0.763, RMSE = 0.972), RF (<i>R</i>^<i>2</i> = 0.634, RMSE = 1.133), and ELM (<i>R</i>^<i>2</i> = 0.533, RMSE = 1.214) models. Finally, the performance of developed models was investigated through comparing with the previous relationships for calculation of earthquake-induced earth slope deformations. The results indicated that the developed machine learning-based predictive models can provide more precise forecasts in comparison to the available recommendation.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental zoning of the Formoso river watershed, Bonito – Mato Grosso do Sul/Brazil","authors":"Rafael Brugnolli Medeiros,&nbsp;Charlei Aparecido da Silva","doi":"10.1007/s12665-025-12479-8","DOIUrl":"10.1007/s12665-025-12479-8","url":null,"abstract":"<div>\u0000 \u0000 <p>Study karst landscapes involves engaging with systems that remain underexplored from an environmental perspective and are increasingly subjected to intensive human activity. These landscapes have been progressively fragmented by monoculture practices, primarily due to the natural fertility associated with limestone-rich soils and the flat terrain that facilitates agricultural expansion. This research proposes an environmental zoning model based on the analysis of landscape units, water quality, and the karst system, aiming to improve watershed management and offer a framework applicable to other karst regions, using as a pilot area that of the Formoso River Watershed (FRW), located in the municipality of Bonito, Brazil, taking into account key landscape components such as lithology, precipitation, topography, soil characteristics, land use and land cover, and water resources. To achieve this, Geographic Information Systems (GIS) were utilized—specifically, ArcGIS 10^® and Spring 5.2.7—for the collection and spatial analysis of environmental indicators. Field surveys were conducted to complement and validate the mapped data, enabling a more detailed and accurate representation of the study area. The results revealed the spatial heterogeneity of the FRW landscape, allowing for the identification of five primary zoning categories: Permanent Preservation Zones, Recovery and Rehabilitation Zones, Special Management Zones, Sustainable Use or Maintenance Zones, and Urban Zones, along with ten subzones. Each of these zones offers a framework for physical-territorial planning in a context marked by rapid land occupation and use, particularly the expansion of soybean cultivation in karst environments. The environmental zoning proposed in this study serves not only as a tool to guide public policy and land management decisions, but also as a contribution to the broader understanding of karst systems. It underscores their environmental fragility and structural complexity, especially under mounting agricultural pressure, and reinforces the need for targeted mitigation strategies and further scientific investigation.</p>\u0000 </div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144810888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kinetic modeling and mechanistic insights into chloroquine phosphate degradation by UV-activated peroxymonosulfate","authors":"Tongtong Jiang,&nbsp;Yang Li,&nbsp;Mingle Xia,&nbsp;Lin Deng,&nbsp;Changbo Zhang,&nbsp;Rajendra Prasad Singh,&nbsp;Gongde Wu","doi":"10.1007/s12665-025-12487-8","DOIUrl":"10.1007/s12665-025-12487-8","url":null,"abstract":"<div><p>Chloroquine phosphate (CQP), a widely utilized antimalarial and anti-COVID-19 medication, exhibits persistence and ecotoxicity in aquatic environments. This study systematically investigated the CQP degradation in the UV-activated peroxymonosulfate (UV/PMS) process, focusing on influencing factors, degradation pathways, and constructs the first-principle kinetic model describing this degradation. The UV/PMS process effectively degraded CQP with a pseudo-first-order reaction rate constant of 0.271 min^− 1, sulfate radicals (SO₄•⁻, 62.4%) and hydroxyl radicals (HO•, 27.3%) were the dominant reactive species. Increasing PMS concentration enhanced radical generation and degradation efficiency. Furthermore, the UV/PMS process exhibited excellent pH adaptability, when the pH value was 10.8, the maximum pseudo-first-order reaction rate constant was 2.894 min^− 1 due to the sharp increase in HO• contribution. Cl⁻ slightly inhibited degradation by consuming SO₄•⁻, while HCO₃⁻ had no obvious effect due to the non-negligible role of CO₃•⁻. Additionally, a kinetic model simulated the radical dynamics and degradation trends, showing a strong correlation with experiments. Several potential degradation pathways involved N-deethylation, C-N bond cleavage, hydrogen abstraction, and N-oxidation. An economic analysis revealed that the total cost reached the minimum of 0.33 USD/(m³∙order) when the concentration of PMS was 0.14 mM. This study provides theoretical support for UV/PMS-based CQP removal from water.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144814285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of flow velocity and concentration on the overtopping failure mechanism of tailings dams","authors":"Kunpeng Zhao,&nbsp;Zhao Deng,&nbsp;Shengshui Chen,&nbsp;Qiming Zhong,&nbsp;Yao Chao,&nbsp;Junfeng Jiang","doi":"10.1007/s12665-025-12483-y","DOIUrl":"10.1007/s12665-025-12483-y","url":null,"abstract":"<div><p>The failure risk of tailings dams has significant impacts on downstream environments and safety. This study investigates the effects of tailings slurry concentration and inflow velocity on the failuring process of tailings dams through physical model experiments. Experiments were conducted under low-, medium-, and high-concentration slurry conditions with varying inflow velocities, focusing on the role of slurry fluidity in failure evolution. Discharge-time curves were analyzed to reveal dynamic characteristics of the dam-break process. Results indicate that as slurry concentration increases, fluidity decreases, prolonging the failuring process and reducing discharge rates. Inflow velocity significantly affects the initial failuring rate, with higher velocities accelerating failure expansion. The study demonstrates that slurry concentration and fluidity critically influence erosive capacity during failuring, particularly under low viscosity conditions where failuring becomes more intense. Higher inflow velocities exacerbate failure development, leading to severe dam erosion. Rational control of slurry concentration and flow velocity can effectively mitigate tailings dam failure processes, reducing downstream hazards. This research provides experimental insights for discharge prediction and disaster mitigation strategies during tailings dam failures.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144814287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single and combined toxicity of copper and cadmium on Microcystis aeruginosa: effects on growth, oxidative stress and gene expression","authors":"Qing Cao,&nbsp;Bensheng You,&nbsp;Haibo Xu,&nbsp;Weijing Liu,&nbsp;Shuzhan Ma","doi":"10.1007/s12665-025-12485-w","DOIUrl":"10.1007/s12665-025-12485-w","url":null,"abstract":"<div><p>Copper (Cu) and cadmium (Cd) are commonly found in polluted water bodies due to intensive anthropogenic activities, but their combined toxicity on <i>Microcystis aeruginosa</i> remains unknown. The present study conducted a 96-h cultivation experiment to investigate the toxicity effects of Cu and Cd, both individually and in mixture, on the growth, oxidative response and gene expression of <i>Microcystis aeruginosa</i>. Results showed that Cd alone had no negative impact on <i>M. aeruginosa</i> growth; whereas growth was significantly inhibited by Cu alone and by the mixture. High concentrations of Cu (200 µg L^− 1) and Cd (50 µg L^− 1), as well as their mixture, induced oxidative stress in <i>M. aeruginosa</i>. The <i>ftsH</i> gene, <i>prx</i> gene, <i>fabZ</i> gene and <i>recA</i> gene were all up-regulated by high concentrations of Cu (200 µg L^− 1), Cd (50 µg L^− 1) and their mixtures (100 + 25 and 200 + 50 µg L^− 1), which however, decreased the expression of the <i>psbA</i> gene. The combined toxicity assessment suggested that synergistic interaction occurred in treatments with low Cu and Cd concentrations (100 + 25 µg L^− 1). Our results suggest that the toxicity effects of Cu and Cd are exacerbated when they co-exist in the natural environment at relatively low concentrations.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145142643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of tree-based ensemble techniques in predicting groundwater quality for irrigation purposes","authors":"Anas El Ouali,&nbsp;Kayhan Bayhan,&nbsp;Rachid Mohamed Mouhoumed,&nbsp;Pınar Spor,&nbsp;Cemre Sude Atan,&nbsp;Eyyup Ensar Başakın,&nbsp;Ömer Ekmekcioğlu","doi":"10.1007/s12665-025-12469-w","DOIUrl":"10.1007/s12665-025-12469-w","url":null,"abstract":"<div><p>This study evaluates the performance of eight different machine learning (ML) methods to predict the Irrigation Water Quality Index (IWQI), an important metric for assessing groundwater quality for agricultural purposes. The study domain was selected as the Saïss Plain in northern Morocco as the region stands out as an area with intense agricultural activities where groundwater quality is of critical importance for irrigation. Groundwater quality is affected by natural factors such as salinity and ion concentrations, as well as anthropogenic activities such as agricultural and industrial practices. Among eight ML approaches, the XGBoost model outperformed its counterparts, including other tree-based ML algorithms and benchmarking models, and yielded the highest prediction accuracy with Nash Sutcliffe Efficiency (NSE) index of 0.963 and 0.892 for training and testing sets, respectively. Other tree-based models such as Random Forest, AdaBoost, and Extra Trees also showed strong performance, while benchmarking models such as ANN, KNN, and SVR were less effective due to the size and non-linear nature of the dataset. The analysis revealed that chloride (Cl⁻) and sodium (Na+) ions are the most critical factors in IWQI estimations. This study highlights the importance of robust ML models in groundwater quality management and provides insights to guide future research for sustainable irrigation practices.</p></div>","PeriodicalId":542,"journal":{"name":"Environmental Earth Sciences","volume":"84 16","pages":""},"PeriodicalIF":2.8,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145142319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}