Environmental Monitoring and Assessment最新文献

{"title":"Soil factors governing shoot metal(loid) concentrations of lettuce and Swiss chard: a multivariate assessment across diffuse soil contamination gradients","authors":"Sibylle Comeliau,&nbsp;Yves Brostaux,&nbsp;Gilles Colinet","doi":"10.1007/s10661-026-16097-0","DOIUrl":"10.1007/s10661-026-16097-0","url":null,"abstract":"<div><p>Diffuse metal(loid) contamination of agricultural soils is a concern for vegetable production in former mining and smelting regions, but the consistency of soil-plant relationships across contrasting soils remains unclear. We examined whether shoot element concentrations of lettuce (<i>Lactuca sativa</i> L.) and Swiss chard (<i>Beta vulgaris</i> L. subsp. <i>vulgaris</i>) show common relationships with soil properties across seven organic market gardens (11 plots) in eastern Belgium, on soils sharing a regional Cd–Pb–Zn enrichment. Two datasets were analyzed: 210 subplots with soil pH and 0.01 M CaCl₂-extractable metals, and 55 subplots with a detailed soil characterization (total, EDTA- and CaCl₂-extractable metal(loid)s, pH, cation exchange capacity, total organic carbon and texture). Soil–shoot relationships were assessed with principal component analysis, redundancy analysis and partial least squares path modeling (PLS-PM). In both crops and datasets, shoot Cd, Mn and Zn followed a common gradient opposing soil pH (4.6–6.4) to CaCl₂-extractable concentrations, and were more closely related to soil acidity than to total contamination (Cd 0.74–5.13 mg · kg⁻¹): Swiss chard from the most contaminated, near-neutral plot had among the lowest shoot Cd. Shoot Pb, Mo, Cu, Fe and Al were weakly coupled to this gradient. PLS-PM showed significant indirect effects of total stocks on shoot concentrations through the extractable pools, and a direct control of soil pH on the CaCl₂-extractable pool. Swiss chard accumulated more Zn and Mn and showed stronger soil–plant relationships, whereas lettuce was more directly responsive to soil pH. Soil pH combined with CaCl₂-extractable Cd, Mn and Zn could help identify plots where transfer to leafy vegetables is likely to be highest and guide soil management.</p><h3>Graphical Abstract</h3>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149338760","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":"A machine learning-based rapid water quality estimation method for stormwater outfalls: A case study in Xiamen, China","authors":"Baozong Wang,&nbsp;Yi Pan,&nbsp;Linhao Xiao,&nbsp;Peigen Lin,&nbsp;Qi Tian,&nbsp;Yanxiang Zhuang,&nbsp;Junmo Tan,&nbsp;Wenting Lin,&nbsp;Jiping Wang,&nbsp;Acong Chen","doi":"10.1007/s10661-026-16126-y","DOIUrl":"10.1007/s10661-026-16126-y","url":null,"abstract":"<div><p>Urban stormwater outfall pollution is characterized by abrupt onset and drastic fluctuations, making it difficult for conventional monitoring methods to achieve rapid response. Taking the typical stormwater outfall in Xiamen as a case study, this research developed a machine learning-based rapid water quality estimation method. Two ensemble learning models, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), were compared, and the Harris Hawks Optimization (HHO) algorithm was introduced for automatic hyperparameter tuning. The results showed that both models performed poorly under default hyperparameters, while HHO optimization significantly improved model accuracy. Specifically, the HHO-XGBoost model achieved <i>R</i>² values of 0.905 and 0.866 for NH₃-N and TN, respectively. Feature importance and SHapley Additive exPlanations (SHAP) analyses revealed that HHO optimization enhances model interpretability by suppressing redundant feature interference and strengthening the weights of dominant variables. Furthermore, by comparing HHO with Random Search and Bayesian Optimization, this study confirmed that HHO possesses stronger global search capability in nonlinear hyperparameter spaces. The findings demonstrate that a machine learning framework driven by easily measurable and real-time monitoring indicators can serve as an effective supplement to existing monitoring systems, providing technical support for trend diagnosis and rapid screening of urban stormwater outfall pollution.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149338691","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":"Effect of the type of anthropogenic impact on soil organic carbon stocks in soils of the Rostov agglomeration","authors":"Suleiman Samidinovich Tagiverdiev,&nbsp;Sergey Nikolaevich Gorbov,&nbsp;Pavel Nikolaevich Skripnikov,&nbsp;Nadezhda Vladimirovna Salnik,&nbsp;Olga Stepanovna Bezuglova","doi":"10.1007/s10661-026-16139-7","DOIUrl":"10.1007/s10661-026-16139-7","url":null,"abstract":"<div><p>This study assesses how different types of anthropogenic impact affect the layer-by-layer distribution of soil organic carbon (SOC) stocks in soils of the Rostov agglomeration. The objects studied were natural Haplic Chernozems under herbaceous and woody phytocenoses, anthropogenically transformed urbic horizons within Urbic Technosols, and the natural buried horizons beneath them. In total, 80 soil pits were described; total, inorganic and organic carbon contents were determined by high-temperature catalytic combustion, and stocks were calculated from bulk density for successive 10 cm layers to a depth of 70 cm. Differences were evaluated using the Mann–Whitney test. Natural Haplic Chernozems under both herbaceous and woody vegetation showed a pronounced four-member vertical stratification of carbon stocks: a surface maximum, a transitional zone of declining organic matter input, an intermediate zone of relative statistical homogeneity, and a distinct lower horizon with minimum stocks; under woody phytocenoses, the boundaries of these zones were displaced to greater depths. Urbic Technosols displayed pseudo-homogenisation from 20 cm downwards with high individual variability, although their median SOC stocks were generally comparable to natural analogues, possibly due to reclamation practices. The most pronounced carbon-pool degradation occurred in Haplic Chernozems buried beneath technogenic deposits: natural stratification was preserved, but absolute stocks were significantly lower than in all other groups, consistent with cessation of fresh organic matter input and depletion of previously sequestered carbon, or with partial removal of topsoil before burial. These results show that anthropogenic impact can both reduce absolute carbon stocks and distort their natural vertical architecture, which must be considered when assessing the carbon sequestration potential of urban soils.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149338692","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":"Removal of endocrine disruptors from tap water: a systematic review","authors":"Paola Rapisarda,&nbsp;Gea Oliveri Conti,&nbsp;Eloise Pulvirenti,&nbsp;Carmela Strazzeri,&nbsp;Alfina Grasso,&nbsp;Maria Castrogiovanni,&nbsp;Margherita Ferrante","doi":"10.1007/s10661-026-16035-0","DOIUrl":"10.1007/s10661-026-16035-0","url":null,"abstract":"<div><p>Endocrine-disrupting chemicals (EDCs) are increasingly detected in drinking water sources due to their widespread use and environmental persistence. Their potential to interfere with hormonal systems, even at trace levels, poses serious concerns for human health, including developmental, reproductive, and metabolic effects. This systematic review aimed to identify and compare the most effective treatment technologies to remove EDCs from drinking water, assessing their performance, analytical approaches, limitations, and relevance to public health and regulatory frameworks. Following PRISMA guidelines, a comprehensive literature search was conducted across 4 databases (PubMed, Scopus, Web of Science, Cochrane Library), resulting in the inclusion of 19 experimental studies published from the last 20 years. The studies were assessed for methodological quality and risk of bias using the Cochrane ROB-2 tool. A wide spectrum of EDCs was studied, including estrogens, per- and polyfluoroalkyl substances (PFAS), bisphenols, parabens, and drug residues, across diverse treatment configurations. Conventional methods (e.g., coagulation, chlorination) have shown limited efficacy; instead, advanced techniques such as ozonation, nanofiltration, activated carbon adsorption, and advanced oxidation processes (AOPs) have mainly achieved removal &gt; 90% for several compounds. Bioassays (e.g., Yeast Estrogen Screen—YES) were used in eligible studies to assess residual estrogenicity. Advanced and hybrid water treatment technologies demonstrate the highest removal efficiency for a range of endocrine disruptors. However, variability in study design and target compounds highlights the need for harmonized protocols and regulatory benchmarks. These findings support the development of more effective drinking water treatment strategies to reduce EDC exposure and protect human health.</p><h3>Graphical abstract</h3>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149338545","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":"Correction to: Letter to the editor “A hybrid machine learning approach to identify potential green cover area for bio–physical suitability mapping in the western semi–arid Rarh region of West Bengal, Purulia” by Manna and Rani 2026, Environmental Monitoring and Assessment, 198, 571","authors":"Eyyup Ensar Başakın","doi":"10.1007/s10661-026-16120-4","DOIUrl":"10.1007/s10661-026-16120-4","url":null,"abstract":"","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149331976","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":"Geochemistry of rare earth and trace elements in the soil of the lesser Zab River Basin, Northeastern Iraq: distribution, fractionation, provenance, and weathering controls","authors":"Younus I. Al-Saady,&nbsp;Salahalddin S. Ali,&nbsp;Arsalan Ahmed Othman,&nbsp;Ibrahim Qasim Mohammed,&nbsp;Ahmed K. Obaid,&nbsp;Syed E. Hasan","doi":"10.1007/s10661-026-16104-4","DOIUrl":"10.1007/s10661-026-16104-4","url":null,"abstract":"<div><p>The study involved textural and geochemical analyses of 25 topsoil samples from the Lesser Zab River Basin, northeastern Iraq, including the source, distribution, and weathering behavior of trace elements (TEs) and rare earth elements (REEs) and their relationship with topsoil texture. Clay loam, silt loam, and silty clay loam are the predominant textures, with quartz, feldspar, calcite, and dolomite as dominant mineral phases and smectite and illite as the main clay minerals. Soils are moderately alkaline with low organic matter and comparatively high Fe₂O₃ content. While most TEs fell below Post-Archean Australian Shale (PAAS) reference values, Cr, Co, and Ni were markedly enriched-locally up to an order of magnitude above background. This enrichment reflects a mafic–ultramafic source distinct from the lithogenic REE factor, linked to ophiolitic contributions. Geo-accumulation index, enrichment factor (EF), and pollution index (PI) values indicated no pollution by Cu, Zn, As, Pb, and Cd; localized high Cr, Co, and Ni (Igeo up to 3.8, EF up to 59, PI up to 21) were linked to ophiolitic outcrops, indicating a geogenic origin of this anomaly. Total REEs averaged 55.92 mg/kg, significantly lower than the North American Shale Composite (NASC) and PAAS values, with LREE enrichment and HREE depletion (PAAS-normalized (La/Yb)_n = 28.76–66.34).</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149309453","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":"Intra-urban variability and meteorological drivers of PM2.5 and PM10 concentrations in an arid Argentine city","authors":"Natalia Andino,&nbsp;Viviana N. Fernández Maldonado","doi":"10.1007/s10661-026-16103-5","DOIUrl":"10.1007/s10661-026-16103-5","url":null,"abstract":"<div><p>Urban air pollution is a major environmental challenge in arid cities, where meteorological conditions strongly influence pollutant accumulation, transport, and dispersion. This study analyzed the relationship between meteorological variables and particulate matter (PM_2.5 and PM₁₀) concentrations in the San Juan Metropolitan Area, an arid urban environment in central western Argentina, over a short-term monitoring campaign during the cold season. Continuous air quality and meteorological monitoring was conducted across residential, industrial, and commercial zones. Generalized additive models (GAMs) were applied to evaluate the effects of air temperature, relative humidity, atmospheric pressure, wind speed, wind direction, and global radiation on PM concentrations. Significant differences in particulate matter concentrations were observed among urban land-use zones, with industrial and commercial zones showing the highest PM_2.5 and PM₁₀ levels, while residential zones presented lower concentrations. Pronounced diurnal variability was also detected, with concentration peaks occurring during morning and evening periods, particularly in commercial and industrial zones. Meteorological variables emerged as key drivers of PM variability, although their influence differed according to particle fraction and urban zone. Atmospheric pressure and wind speed were the most influential predictors across most models, emphasizing the role of atmospheric stability and ventilation processes in regulating PM accumulation and dispersion. PM_2.5 was more sensitive to stable atmospheric conditions and low wind speeds, whereas PM₁₀ was more strongly associated with wind-related resuspension processes. These findings provide new insights, based on a short-term monitoring campaign, into meteorological controls of particulate matter in arid urban environments and may support the development of effective air quality management strategies in regions with similar climatic and urban characteristics.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149316948","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":"Assessing fire severity patterns and carbon sink capacity changes following the 2021 Manavgat wildfire using remote sensing and Google Earth Engine","authors":"Halil Duymuş","doi":"10.1007/s10661-026-16115-1","DOIUrl":"10.1007/s10661-026-16115-1","url":null,"abstract":"<div><p>Wildfires can impair vegetation productivity well beyond the fire year, yet the persistence and monetary implications of these deficits remain poorly characterised in Mediterranean landscapes. This study integrates Sentinel-2 burn-severity mapping, MODIS annual net primary production (NPP), an adjacent unburned-forest comparison, and scenario-based valuation to assess the 2021 Manavgat wildfire in Türkiye. A MODIS burned-area event envelope covered 424 km², including 270 km² of pre-fire forest; valid paired Sentinel-2 observations supported severity classification across 246.26 km². Burn-severity thresholds derived from the study-area differenced Normalized Burn Ratio (dNBR) distribution were 0.316 and 0.613. Relative to the 2016–2020 mean (0.830 kg C m⁻² yr⁻¹), burned-forest NPP declined to 0.621 in 2021 and 0.440 in 2022, then increased to 0.705 in 2023 and 0.710 in 2024. A difference-in-differences comparison with nearby unburned forest indicated persistent productivity deficits beyond shared temporal variability. The estimated cumulative productivity-based carbon sink deficit for 2021–2024 was 227,150 t C (832,885 t CO₂e). Valuation was approximately USD 158.2 million under the central social cost of carbon scenario and EUR 60.5 million using annual EU Allowance prices. These findings demonstrate the value of integrating severity, productivity trajectories, and economic scenarios for post-fire monitoring and restoration prioritisation.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149316947","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":"Assessment of natural radioactivity and heavy metal pollution risks in Lake Arin, Türkiye","authors":"Şule Karatepe Çelik,&nbsp;Sultan Şahin Bal","doi":"10.1007/s10661-026-16138-8","DOIUrl":"10.1007/s10661-026-16138-8","url":null,"abstract":"<div><p>This study assessed natural radioactivity and heavy metal pollution in water samples collected from Lake Arin, Türkiye. A total of 27 samples were analyzed for ²²⁶Ra, ²³²Th, and ⁴⁰ K activity concentrations using gamma-ray spectrometry, while heavy metal concentrations were determined to evaluate the environmental quality of the lake water. The mean activity concentrations of ²²⁶Ra, ²³²Th, and ⁴⁰ K were 0.44 ± 0.02 Bq L⁻¹, 0.66 ± 0.03 Bq L⁻¹, and 4.98 ± 0.08 Bq L⁻¹, respectively. The mean activity concentrations of ²²⁶Ra and ²³²Th were below the reference values used for comparison, whereas the mean ⁴⁰ K activity concentration was slightly higher than the comparative value reported in the literature. Hierarchical cluster analysis revealed differences in radionuclide profiles among the sampling points. Heavy metal pollution was also low, as confirmed by HPI values ranging from 8.165 to 8.929 and HEI values ranging from 0.197 to 0.254. Although the current levels of natural radioactivity and heavy metals in Lake Arin water are generally low, continued environmental monitoring is necessary to protect the ecological integrity of this sensitive wetland ecosystem.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149309452","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":"Unraveling the nonlinear relationships between blue-green spatial patterns and carbon sequestration through an interpretable XGBoost-SHAP model","authors":"Xianjin Zhang,&nbsp;Bo Nan,&nbsp;Qingxin Zhang,&nbsp;Na Yao,&nbsp;Hongjie Wang","doi":"10.1007/s10661-026-16091-6","DOIUrl":"10.1007/s10661-026-16091-6","url":null,"abstract":"<div><p>Blue-green spaces (BGS) play a critical role in contributing to both direct carbon sequestration (CS) and indirect carbon reduction. However, the relationship between blue-green spatial patterns (BGSPs) and CS remains insufficiently explored. This study developed an analytical framework to investigate the nonlinear relationship between BGSP and CS. In this framework, morphological spatial pattern analysis (MSPA) and landscape pattern indices were used to characterize BGSP; the Carnegie-Ames-Stanford approach (CASA) model estimated net primary productivity (NPP) as a proxy for CS; and the eXtreme gradient boosting-SHapley additive exPlanations (XGBoost-SHAP) model was employed to reveal the underlying nonlinear relationships between BGSP metrics and NPP. Hebei Province, China, was selected as a representative case study. The results indicate that BGSPs are significantly associated with CS, with the strength of the association varying across different features. Core and percentage of landscape (PLAND) are the dominant predictors of CS, both showing positive associations with NPP. Large and continuous blue-green patches are essential for maintaining high CS, whereas small, fragmented, and isolated patches contribute relatively little. Boundary length and shape complexity are positively associated with CS above specific thresholds. Moderate fragmentation may be weakly beneficial to CS. Significantly higher NPP is associated with PLAND above 80, core above 60, LSI above 2, ED above 30, edge above 20, AI below 97.5, and SPLIT above 20. These findings provide a scientific basis for optimizing regional BGSP and inform spatial planning and ecological management strategies aimed at enhancing CS. Furthermore, the proposed framework offers a transferable methodological reference for investigating nonlinear relationships between BGSP and CS in other regions.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"198 12","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149309880","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}