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基于APCS-MLR和PMF模型的平安盆地土壤重金属源解析 认领 引用 被引量：4
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作者 张亚峰 施泽明 +5 位作者 苗国文 许光 强晓农 金戈 马风娟 姚振 《环境科学》 EI CAS CSCD 北大核心 2026年第5期3414-3424,共11页
为查明平安盆地土壤重金属本底特征,识别供源类型,以区内3006组土壤的Cd、Hg、As、Pb、Cr、Cu、Zn和pH检测值为基础,选用组合评价方法对富集状况及潜在生态风险进行分析,用APCS-MLR和PMF模型确定土壤重金属源类型.结果表明:①研究区土... 为查明平安盆地土壤重金属本底特征,识别供源类型,以区内3006组土壤的Cd、Hg、As、Pb、Cr、Cu、Zn和pH检测值为基础,选用组合评价方法对富集状况及潜在生态风险进行分析,用APCS-MLR和PMF模型确定土壤重金属源类型.结果表明:①研究区土壤Hg和Pb低于中国土壤背景值,Cu、Zn、Cr、Cd和As高于中国土壤背景值.Hg在湟水河沿河人类活动区有一定外源性输入;As有6%的点位超过风险管控值,多处在南部山区,对耕地影响小.②从潜在生态风险看,Pb和Zn的E值均小于40,无生态风险;Cr和Cu有少量中度生态风险点,生态风险低;Hg、Cd和As有中高度生态风险点,有一定风险存在,且呈现Hg>Cd>As的特征.研究区生态风险RI均值为102,整体呈低风险.③APCS-MLR和PMF模型互为补充和验证,共同解析出研究区主要存在的4种重金属源.即硫化物主导型自然源、地幔物质主导型自然源、表生改造型自然源和人类活动干扰源.研究结果为研究区重金属风险预防和生态治理工程选定提供了技术支撑,对青藏高原典型区重金属演化及生态效应研究具有指导意义. 展开更多
关键词 平安盆地 富集特征 APCS-MLR模型 PMF模型 源解析
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基于PMF和机器学习模型的蒸水中下游流域农田土壤重金属污染状况及来源解析 认领 引用 被引量：3
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作者 董天浩 任传猛 +7 位作者 任清盛 董贝 张仁杰 李承永 潘淑芳 郭焱 纪雄辉 谢运河 《农业环境科学学报》 CAS CSCD 北大核心 2026年第1期69-81,共13页
为了探究湘江支流蒸水中下游流域农田土壤重金属污染风险,对蒸水中下游流域农田土壤进行了采样分析及污染源解析。结果表明:该区域土壤存在较大的Cd污染风险,部分存在As、Pb和Cu污染风险。研究区识别出4个污染源,即自然-大气沉降混合源... 为了探究湘江支流蒸水中下游流域农田土壤重金属污染风险,对蒸水中下游流域农田土壤进行了采样分析及污染源解析。结果表明:该区域土壤存在较大的Cd污染风险,部分存在As、Pb和Cu污染风险。研究区识别出4个污染源,即自然-大气沉降混合源、自然源、大气沉降源和工业源。PMF模型判定土壤As和Hg主要受自然-大气沉降混合源的影响,Cr、Ni和Cu主要受自然源影响,Pb主要受大气沉降源影响,Cd和Zn主要受工业源影响;4个污染源的贡献率依次为30.8%、27.0%、22.6%和19.6%。SOM模型污染源分类结果与PMF模型源解析结果均吻合度较高。LightGBM模型结果表明距蒸水主流距离对Cd、Pb、Ni和Zn的影响均较大,PM2.5浓度对Cd和Pb的影响较大;对As、Hg和Cr影响最大的因子均为母岩类型;与交通相关的因子对Cu和Zn的影响较大。研究表明,该研究区农田土壤有一定的重金属污染风险,且污染来源较复杂,LightGBM模型可对PMF模型结果进行一定程度的补充,受体模型结合机器学习模型能够更合理地判别各土壤重金属主要的污染来源。 展开更多
关键词 土壤重金属 源解析 PMF模型 SOM模型 LightGBM模型
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基于PMF模型和机器学习模型的金属冶炼园区周边农田土壤重金属污染来源解析 认领 引用 被引量：4
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作者 张峥 孙东越 +3 位作者 邹霖 王鹏 姜晓旭 封雪 《环境科学》 EI CAS CSCD 北大核心 2026年第4期2604-2611,共8页
探究多种土壤重金属溯源方法,定量掌握土壤重金属污染特征,对土壤污染防控有着重要意义.以湖南某金属冶炼园区周边土壤为研究对象,对土壤中Cd、As、Pb、Cu和Zn等5种重金属元素进行分析,使用地累积指数评价土壤污染程度,利用空间分布、... 探究多种土壤重金属溯源方法,定量掌握土壤重金属污染特征,对土壤污染防控有着重要意义.以湖南某金属冶炼园区周边土壤为研究对象,对土壤中Cd、As、Pb、Cu和Zn等5种重金属元素进行分析,使用地累积指数评价土壤污染程度,利用空间分布、正定矩阵因子分解模型(PMF)和支持向量回归-可解释性模型(SVR-SHAP)进行源解析.土壤重金属污染评价结果表明,园区周边土壤中5种重金属均存在污染风险,其中Cd和As风险最高.基于PMF模型的源解析识别出2个污染来源,即人为源和自然源,对土壤重金属贡献率分别为53.16%和46.84%.PMF模型判定土壤Cu和Zn主要受自然源影响,Cd、As和Pb主要受人为源影响.结合园区生产活动、周边情况及SVR-SHAP模型进一步解析土壤污染来源.结果表明,土壤Cd污染主要来自于冶炼活动和农业活动,As污染主要来自于冶炼活动和化石燃料燃烧,Pb污染主要来自于冶炼活动、废渣堆放和农业活动.研究结果表明,该金属冶炼园区周边区域农田土壤存在较大的重金属污染风险,联合使用两种模型能够更合理地判别土壤重金属主要的污染来源. 展开更多
关键词 重金属 源解析 正定矩阵因子分解(PMF) 机器学习 金属冶炼园区
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基于PMF模型和Pb同位素示踪的土壤重金属污染现状分析及源解析 认领 引用 被引量：3
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作者 王大可 徐立明 +6 位作者 郑吉林 闭向阳 姚宇 蔡艳龙 郭晓宇 刘军帅 谭博文 《地质通报》 CAS CSCD 北大核心 2026年第2期391-407,共17页
【研究目的】为精准识别城市土壤重金属混合污染来源并验证模型解析结果的可靠性,以黑龙江省哈尔滨市土壤为研究对象,通过多维度数据融合与Pb同位素指纹技术,系统揭示土壤重金属分布特征与来源贡献,以期为城市土壤污染防控提供科学依据... 【研究目的】为精准识别城市土壤重金属混合污染来源并验证模型解析结果的可靠性,以黑龙江省哈尔滨市土壤为研究对象,通过多维度数据融合与Pb同位素指纹技术,系统揭示土壤重金属分布特征与来源贡献,以期为城市土壤污染防控提供科学依据。【研究方法】在研究区采集60个土壤样品,测定土壤Pb同位素、重金属Cr、Mn、Co、Ni、Cu、Zn、Cd、As、Pb元素总量及表层土壤形态总量。通过重金属的空间分布特征、多元统计分析和同位素示踪等,分析该区域重金属污染程度和污染来源。【研究结果】研究区土壤重金属Cr、Mn、Co、Ni、Cu、Zn、Cd、As、Pb元素平均含量分别为55.2 mg/kg、651 mg/kg、9.63 mg/kg、23.7 mg/kg、31.0 mg/kg、119 mg/kg、16.1 mg/kg、0.35 mg/kg、45.6 mg/kg,Mn、Zn、Cd的酸可提取态占总量相对较高,表明这3种元素活性最强,对环境的影响最大。在空间分布上,Cu、Zn、Cd和Pb元素在生活区含量最高,且具有相似的高值分布点,Cr、Mn、Co和Ni元素在空间分布上相对均匀。【结论】通过PMF受体模型发现,研究区35%的Mn、35%的As、33%的Pb来自煤炭燃烧;45%的Zn、32%的Cd来自交通排放;73%的Cu、43%的Zn、35%的Pb来自工业生产;55%的Ni、48%的Co、47%的Cr、41%的As来自成土母质。土壤中Pb同位素比值结果表明,土壤中Pb人为来源可能主要来自工业排放(包括燃煤排放和矿石冶炼)。 展开更多
关键词 重金属污染 PMF模型 多元统计分析 Pb同位素 空间分布特征 黑龙江
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Evolution process and controlling factors of gas content in marine-continental transitional shales:Insights from numerical modeling 认领 引用
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作者 Xiao-Guang Yang Shi-Zhen Li +2 位作者 Qiu-Chen Xu Fei Li Xiang-Lin Chen 《Petroleum Science》 SCIE EI CAS CSCD 2026年第5期2330-2347,共18页
Marine-continental transitional shale(McTS)gas holds excellent gas-generating hydrocarbon basis and exploration potential.Conducting quantitative analysis on the evolution of shale gas content and the coupled relation... Marine-continental transitional shale(McTS)gas holds excellent gas-generating hydrocarbon basis and exploration potential.Conducting quantitative analysis on the evolution of shale gas content and the coupled relationship between hydrocarbon generation and storage during geological history is essential for a profound understanding of shale gas enrichment mechanisms.This studyestablishes integrated models for hydrocarbon generation evolution,porosity evolution,and gas occurrence in Type Ill organicrich MCTS through a synergistic experimental approach combining multi-temperature methane isothermal adsorption experiments andgold-tube pyrolysis experiments on low-maturity shale samples.Simulating a variety of real and virtual burial histories and thermal histories,the evolution process ofgas content in McTSwas reconstructed and the influence of various geological conditions during burial on gas content evolution was clarified.The results indicate that a seven-stage evolution(AG)of gas content in McTS from the Shanxi Formation,Southern North China Basin.Critical thresholds include:(1)dissolution-enhancedreservoir modification at vitrinite reflectance(EasyRo)=1.0%,(2)adsorbed gas saturation at EasyRo=1.3%,(3)dual saturation of free andadsorbedgas at EasyRo=2.0%,(4)15%30%gas loss through expulsion during overmature stages(EasyRo>2.0%),and(5)partial freeto-adsorbed gas conversion triggered by tectonic uplift.Total organic carbon(ToC)content and overpressure exhibit positive correlations with gas content,while tectonic uplift magnitude shows a negative impact.The influence of maximum burial depth,paleo-heat flow,andgeothermalgradient demonstrate complex nonlinear relationships on gas content. 展开更多
关键词 Shale gas Marine-continental transitional facies Gas content model Evolutionary process Controlling factors
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Attitude-constrained interactive multi-model factor graph fusion for integrated navigation 认领 引用
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作者 Xiao LIANG Pengyu ZHAO +3 位作者 Sitong LIU Baojin LIU Longzhi NIE Chuanjun LI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第3期91-105,共15页
Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation bas... Continuous and highly accurate navigation of long-endurance flight vehicles continues to be a substantial challenge in Global Navigation Satellite Systems(GNSS)-denied environments.Though the integrated navigation based on multiple sensors is used to improve the navigation performance,the existing methods are prone to model mismatch and error accumulation under heterogeneous conditions of sensors.In this paper,a Tightly-coupled Interactive Multi-Model Factor Graph Optimization(TIMMFGO) navigation method is proposed to solve the problem.The developed integrated navigation framework consists of Inertial Navigation Systems(INS),Celestial Navigation Systems(CNS),Radio Navigation Systems(RNS),and Barometric Altimeters(BA).We propose a CNS/INS tightly-coupled graph architecture that integrates star vector observations with INS pre-integration,enabling dynamic compensation of gyroscopic bias while correcting the attitude update accuracy of INS.Then,an Interactive Multi-Model(IMM) adaptive weighting strategy is used to combine the vertical RNS factor with the BA factor for position,which can effectively reduce the altitude bias induced by the spatial configuration constraints of RNS.The simulation demonstrates that compared to the Huber M-estimation-based FGO(HMFGO),Windowing Anomaly-Detection-based FGO(WADFGO) and IMM Unscented Kalman Filter(IMMUKF)methods,the TIMMFGO method improves attitude accuracy by 46.49 %,25.68 % and 20.67 %,respectively,while correspondingly reducing position accuracy by 29.29 %,10.79 % and 6.96 %. 展开更多
关键词 Attitude-constrained position Factor graph optimization IMU pre-integration Interactive multiple models Multi-sensor integrated navigation
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Construction and validation of a predictive model for the risk of emergence delirium in older adult patients 认领 引用
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作者 Yi Xin Bin He +7 位作者 Xiao-Hui Wei Ya-Ling Yan Chen Huang Chun-Yan Gao Shuo Wang Guang-Ming Zhang Rui Li Ying Wu 《World Journal of Psychiatry》 SCIE 2026年第6期389-405,共17页
BACKGROUND Emergence delirium(ED)is a common postoperative complication in older adult patients,posing a significant burden on both patients and medical staff.Despite its prevalence,there is a notable lack of research... BACKGROUND Emergence delirium(ED)is a common postoperative complication in older adult patients,posing a significant burden on both patients and medical staff.Despite its prevalence,there is a notable lack of research focused on identifying predictive factors and constructing models for ED in the post-anesthesia care unit.Therefore,developing a risk prediction model for ED in older adult patients is imperative.We anticipate that such a model would demonstrate strong predictive efficacy and be applicable in clinical settings.AIM To develop and validate an ED risk-prediction model for early intervention in older adults.METHODS This study enrolled 705 older surgical patients(January 2024 to October 2024)for modeling and 115(November 2024 to December 2024)for validation.Using least absolute shrinkage and selection operator and multivariable logistic regression,we developed a predictive model with an online dynamic nomogram.Internal(10-fold crossvalidation)and external validation demonstrated strong discrimination,calibration,and clinical utility.RESULTS The incidence of ED in older adult patients postoperatively was found to be 17.16%.Independent risk factors for postoperative ED included preoperative Mini-Mental State Examination score,preoperative albumin level,surgical duration,surgical risk score,number of indwelling catheters,and extubation time(all P<0.05).The model demonstrated the area under curve(AUC)of 0.924[95%confidence interval(CI):0.897-0.951],with the calibration curve closely aligning with the ideal curve.The Hosmer-Lemeshow test yieldedχ2=7.934,P=0.541,indicating good clinical utility.Internal validation resulted in an AUC of 0.920(95%CI:0.571-0.959),while external validation showed an AUC of 0.931(95%CI:0.866-0.997).The calibration curve for the validation cohort closely matched the ideal curve,with the Hosmer-Lemeshow test showingχ2=5.772,P=0.763,further supporting its clinical applicability.CONCLUSION The dynamic nomogram accurately predicts ED risk in older adults,aiding early identification and clinical intervention. 展开更多
关键词 Older adult Emergence delirium Risk factors Prediction model Nomogram
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Glacial melting impact on runoff and evapotranspiration based on glacier-coupled SWAT model:A case study in the upper Shiyang River Basin,China 认领 引用
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作者 CHU Jiangdong SU Xiaoling +6 位作者 WANG Lei WU Nan Komelle ASKARI WU Haijiang ZHANG Te XU Liujia ZHANG Qifei 《Journal of Arid Land》 SCIE CAS CSCD 2026年第2期216-234,共19页
Glacial meltwater constitutes a vital component of the water supply in arid and semi-arid areas.However,the influence of glacial melting on runoff and evapotranspiration under global warming remains insufficiently und... Glacial meltwater constitutes a vital component of the water supply in arid and semi-arid areas.However,the influence of glacial melting on runoff and evapotranspiration under global warming remains insufficiently understood.Previous studies coupling the Soil and Water Assessment Tool(SWAT)model with glacier modules often failed to consider the spatial heterogeneity of temperature during glacial melting,potentially leading to biased estimates of meltwater volume.In this study,we developed a glacier-coupled SWAT(SWAT-glacier)model considering the digital elevation model(DEM)based temperature-driven glacial melt processes to elucidate the impact of glacial melting on hydrological processes across four river basins(Dongda,Xiying,Jinta,and Zamu)of the upper Shiyang River Basin(SYRB)in northwestern China from 1986 to 2021.Compared with the standard SWAT model,the proposed SWAT-glacier model significantly improved the simulation accuracy for both runoff and evapotranspiration.Specifically,in comparison with the standard SWAT model,the Nash-Sutcliffe efficiency of the SWAT-glacier model showed a relative improvement of approximately 0.42%–9.16%and 1.50%–10.15%for runoff and evapotranspiration,respectively,in the four river basins during the validation period.Annual glacial runoff occurred predominantly from May to October,whereas glacial melt-induced evapotranspiration peaked between June and August.From 1986 to 2021,the average contributions of glacial melt to runoff were 6.97%for Dongda,3.06%for Xiying,2.70%for Jinta,and 0.67%for Zamu,whereas its contributions to evapotranspiration were 9.06%,5.14%,3.21%,and 1.59%,respectively.This study presents a SWAT-glacier modeling framework that enhances the simulation of hydrological processes in cold regions.The proposed methodology can be extended to other glacierized basins to provide valuable insights into water resource management under climate change. 展开更多
关键词 glacial melting Soil and Water Assessment Tool(SWAT) SWAT-glacier model degree-day factor climate change Shiyang River Basin
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Risk factors and prediction model for acute respiratory distress syndrome in patients with digestive tumor after surgery 认领 引用
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作者 Jie Zhen Wei Chen +1 位作者 Yi-Fei Xu Ying-Min Ma 《World Journal of Gastrointestinal Surgery》 SCIE 2026年第1期99-110,共12页
BACKGROUND Postoperative acute respiratory distress syndrome(ARDS)after digestive tumors is a serious complication that severely affects patients’prognosis;however,systematic studies assessing its risk factors are la... BACKGROUND Postoperative acute respiratory distress syndrome(ARDS)after digestive tumors is a serious complication that severely affects patients’prognosis;however,systematic studies assessing its risk factors are lacking,and effective prediction models are urgently required.AIM To investigate the risk factors for postoperative ARDS in patients with digestive tumors and construct a prediction model.METHODS Overall,42 of the 176 patients developed ARDS,with an incidence rate of 23.86%.Multifactorial logistic regression analysis identified advanced age[odds ratio(OR)=1.24,P<0.001],smoking history(OR=3.17,P=0.012),preoperative lung infection(OR=3.07,P=0.015),low preoperative albumin level(OR=0.71,P=0.003),preoperative percentage of forced expiratory volume in 1 second,(OR=0.96,P=0.006),preoperative percentage of forced vital capacity(OR=0.94,P=0.012),and postoperative anastomotic fistula(OR=4.55,P=0.022)as independent risk factors for postoperative ARDS.The nomogram prediction model showed good discriminatory power[area under the curve(AUC)=0.86]and goodness of fit(Hosmer-Lemeshow,P=0.729).The internal validation demonstrated an AUC of 0.86 and a good calibration curve fit(Hosmer-Lemeshow,P=0.914).Prospective clinical validation confirmed the reliability and clinical value of the model(AUC=0.91,accuracy=82.35%).RESULTS Overall,42 of the 176 patients developed ARDS,with an incidence rate of 23.86%.Multifactorial logistic regression analysis identified advanced age(OR=1.24,P<0.001),smoking history(OR=3.17,P=0.012),preoperative lung infection(OR=3.07,P=0.015),low preoperative albumin level(OR=0.71,P=0.003),preoperative percentage of forced expiratory volume in 1 second,(OR=0.96,P=0.006),preoperative percentage of forced vital capacity(OR=0.94,P=0.012),and postoperative anastomotic fistula(OR=4.55,P=0.022)as independent risk factors for postoperative ARDS.The nomogram prediction model showed good discriminatory power(AUC=0.86)and goodness of fit(Hosmer-Lemeshow,P=0.729).The internal validation demonstrated an AUC of 0.86 and a good calibration curve fit(Hosmer-Lemeshow,P=0.914).Prospective clinical validation confirmed the reliability and clinical value of the model(AUC=0.91,accuracy=82.35%).CONCLUSION The nomogram prediction model based on independent risk factors for postoperative ARDS in patients with digestive tumors demonstrated good differentiation,calibration,and clinical utility and helped identify high-risk patients early. 展开更多
关键词 Digestive tumor Acute respiratory distress syndrome Risk factors Prediction model Surgery Clinical value
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融合环境先验信息的BP-PMF源解析模型——以抗生素为例 认领 引用
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作者 张梦园 冯民权 +1 位作者 周洣汝 陈秋禹 《环境科学学报》 CAS CSCD 北大核心 2026年第5期464-477,共14页
传统受体模型常因忽略污染源与环境驱动因子间的非线性关联,导致解析结果物理解释性不足,难以支撑流域精准治污.为此,本研究将地理空间环境以先验信息引入数据驱动模型,提出BP-PMF耦合模型,并以石川河流域的抗生素污染为例进行源解析.... 传统受体模型常因忽略污染源与环境驱动因子间的非线性关联,导致解析结果物理解释性不足,难以支撑流域精准治污.为此,本研究将地理空间环境以先验信息引入数据驱动模型,提出BP-PMF耦合模型,并以石川河流域的抗生素污染为例进行源解析.结果显示,石川河流域抗生素污染中喹诺酮类普遍检出率高且浓度占比较高,优化后的模型对污染源贡献进行了结构性调整:医疗废水贡献由14.9%显著提升至25.7%,跃升为第二大来源;畜禽养殖贡献则从30.4%大幅降至16.6%,退居第三位;水产养殖贡献由6.4%增至10.1%;污水处理厂尾水贡献由8.9%略降至8.4%,农业土壤径流贡献由39.4%微降至39.2%,仍为最主要来源.该调整在稳定识别主导面源的同时,有效纠正了传统模型对医疗废水等点源的低估,建议在持续加强农业面源管理的同时,亟需将医疗机构废水纳入重点监管对象. 展开更多
关键词 抗生素 正定矩阵分解(PMF) BP神经网络 来源解析 环境驱动因子
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基于PMF模型的襄阳某典型工业园区周边农田土壤重金属污染评价及来源解析 认领 引用
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作者 魏国芬 罗德伟 +7 位作者 胡青锋 徐雯 胡芹芹 杨梦 王涛 王秋敏 冷喆 林森 《中国无机分析化学》 CAS 北大核心 2026年第7期1207-1219,共13页
为评估典型工业园活动对周边农田的生态影响,本研究以襄阳市某典型工业园区周边农用土壤为对象,系统采集65个表层土壤样品,测定土壤中8种重金属(Cd、Hg、As、Cr、Cu、Ni、Pb和Zn)含量。综合运用单因子污染指数、地累积指数、内梅罗综合... 为评估典型工业园活动对周边农田的生态影响,本研究以襄阳市某典型工业园区周边农用土壤为对象,系统采集65个表层土壤样品,测定土壤中8种重金属(Cd、Hg、As、Cr、Cu、Ni、Pb和Zn)含量。综合运用单因子污染指数、地累积指数、内梅罗综合污染指数、污染负荷指数及潜在生态风险指数等多种方法评价了工业园区周边农用土壤污染程度与生态风险;并借助GIS空间插值法揭示了重金属的空间分布格局,结合Pearson相关性分析与正定矩阵因子分解(PMF)受体模型定量解析污染来源。分析结果显示:研究区域内8种重金属在土壤中的平均含量均未超过GB 15618—2018规定的风险筛选值,表明土壤环境质量整体处于良好水平。然而,Cd平均含量值为湖北土壤背景值的1.65倍,与Hg一同被视为优先管控污染物。在空间分布上,Cd、Zn高浓度区主要集中于工业园区东南部,而Pb、As高浓度区则沿国道分布,显示出人类活动影响的显著空间分异特征。PMF模型源解析结果表明,研究区土壤重金属主要源于四个方面:自然源和农业源的混合源(31.4%)、工业排放源(27.1%)、交通排放源(22.1%)和燃煤排放源(19.4%)。综上所述,Cd和Hg是研究区内优先管控的污染物,其富集主要分别源于工业排放和燃煤排放。因此,实施以控制工业与燃煤污染为重点的精准防控策略,对保障该区域农田土壤环境安全具有重要意义。 展开更多
关键词 工业园区 土壤重金属 污染评价 PMF模型 来源解析
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基于PMF的河南省新乡市城市周边耕地土壤重金属来源解析 认领 引用
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作者 张妍 谷志云 +2 位作者 赵新雷 裴瑞亮 杨运召 《地质与勘探》 CAS CSCD 北大核心 2026年第4期901-909,共9页
河南省新乡市是我国小麦主产区和重要电池生产基地。为查明城市周边耕地土壤重金属污染状况及来源,本文采集新乡市表层土壤样品(0~20 cm)93件,综合运用多元统计与空间插值等方法分析了As、Cd、Cr、Cu、Hg、Ni、Pb、Zn共8种重金属的含量... 河南省新乡市是我国小麦主产区和重要电池生产基地。为查明城市周边耕地土壤重金属污染状况及来源,本文采集新乡市表层土壤样品(0~20 cm)93件,综合运用多元统计与空间插值等方法分析了As、Cd、Cr、Cu、Hg、Ni、Pb、Zn共8种重金属的含量和空间分布特征,并结合相关性分析和正定矩阵因子分解(PMF)模型解析其来源。结果表明,研究区土壤中As、Cd、Cr、Cu、Hg、Ni、Pb、Zn的中位值分别为11.78 mg·kg-1、0.44 mg·kg-1、70.30 mg·kg-1、29.10 mg·kg-1、0.067 mg·kg-1、32.50 mg·kg-1、31.10 mg·kg-1及80.10 mg·kg-1,均高于全国背景值和河南省背景值。经过与《土壤环境质量农用地土壤污染风险控制标准(试行版)》(GB15618-2018)的对比,结果显示38个样品中Cd含量超标,污染问题突出。空间分布显示,Cd与Ni高值区集中于研究区中心,Cu、Hg、Pb、Zn高值区分布于西部,As高值区位于北部。PMF模型共识别出5种污染来源及其贡献率:农业污水灌溉和交通复合源(31.81%)、农业源(21.23%)、自然源(16.5%)、工业源(15.33%)及燃烧源(15.13%)。研究结果显示,As的积累主要来源于农业活动中化肥的施用;Cd和Ni主要来源于电池生产等工业活动;Cu、Pb、Zn主要受交通排放影响;Cr主要来源于成土母质等自然因素;Hg主要受煤炭燃烧影响。总体而言,工业活动和污水灌溉是该地区土壤重金属的主要贡献者,镉污染风险尤为突出,需针对性加强污染源管控。 展开更多
关键词 土壤重金属 正定矩阵因子分解(PMF) 主成分分析 源解析 新乡市 河南省
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石家庄平原区地下水污染源解析与驱动因素研究——基于PMF与PSO-AdaBoost算法 认领 引用
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作者 刘洋 夏迎秋 +1 位作者 胡应菊 季佳运 《河北地质大学学报》 2026年第3期77-86,共10页
为系统评估石家庄平原区浅层地下水水质并解析硝酸盐氮(NO3-N)及部分阴离子污染来源与驱动因素,研究采集41个浅层地下水样本,采用改进的内梅罗指数法评价水质,通过正定矩阵因子分析(PMF)模型识别污染源,结合粒子群优化-自适应提... 为系统评估石家庄平原区浅层地下水水质并解析硝酸盐氮(NO3-N)及部分阴离子污染来源与驱动因素,研究采集41个浅层地下水样本,采用改进的内梅罗指数法评价水质,通过正定矩阵因子分析(PMF)模型识别污染源,结合粒子群优化-自适应提升算法(PSO-Adaboost)与SHAP方法量化环境因子驱动作用。结果显示,31.71%的样本未达Ⅲ类水质标准,NO3-N超标率29.27%,其次为S和Cl-,三者空间分布呈西高东低特征,改进的内梅罗指数法表明63.41%的样本水质较差。PMF模型识别出工矿活动源(29.26%)、生活-农业复合源(41.78%)和水岩相互作用源(28.96%),生活-农业复合源为主要污染源。环境因子分析表明土壤水分和人口密度是该复合源的核心驱动因子,因此应加强城乡污水收集与处置并优化灌溉管理。 展开更多
关键词 地下水 源解析 驱动因素 石家庄平原区 正定矩阵因子分析 粒子群优化-自适应提升算法
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Research on streamflow and hydrological drought in lower Songhua River Basin under CMIP6 scenarios based on SWAT model 认领 引用
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作者 ZHAO Yusu SUN Yingna +2 位作者 MENG Fanxiang LIU Tao HUANG Xihao 《水利水电技术（中英文）》 CSCD 北大核心 2026年第5期52-67,共16页
[Objective]This study aims to investigate streamflow variations and hydrological drought characteristics in the lower Songhua River Basin under future climate scenarios,providing a scientific basis for regional water ... [Objective]This study aims to investigate streamflow variations and hydrological drought characteristics in the lower Songhua River Basin under future climate scenarios,providing a scientific basis for regional water resource management and guidance for formulating comprehensive drought and flood disaster prevention and control strategies.[Methods]Based on hydrometeorological data from 1970—2014,a SWAT model was constructed and driven by 14 CMIP6 climate models.Five optimal climate models were selected through Taylor diagram analysis and combined with SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios to simulate streamflow variations from 2015 to 2100.[Results]The SWAT model demonstrated excellent performance at Tongjiang hydrological station,with R 2 and NSE values exceeding 0.7 during both calibration and validation periods.The absolute values of PBIAS were below 10.7%,confirming model reliability.Future climate predictions indicated increasing trends in precipitation,temperature,and evapotranspiration across the river basin.The magnitude of temperature and evapotranspiration increases followed the order of SSP5-8.5>SSP2-4.5>SSP1-2.6,while precipitation increases ranked as SSP5-4.5>SSP1-2.6>SSP2-8.5.Seasonally,SSP1-2.6 and SSP5-8.5 scenarios showed significant precipitation increases in autumn and winter,while SSP2-4.5 scenario exhibited notable increases in summer and winter.Streamflow variations strongly depended on scenarios:SSP1-2.6 showed significant increases,while variations under SSP2-4.5 and SSP5-8.5 were not significant.Standardized Streamflow Index(SSI)analysis showed significant increases under SSP1-2.6,but declining trends under other scenarios.Drought characteristic analysis indicated that under SSP1-2.6,all drought indices except average drought duration decreased,while under SSP2-4.5 and SSP5-8.5,all indices except drought frequency increased.Seasonally,SSP1-2.6 increased spring-summer proportions with elevated winter drought frequency,while SSP2-4.5 and SSP5-8.5 increased autumn-winter proportions with corresponding frequency changes.[Conclusion]Future climate change will significantly impact hydrological characteristics in the lower Songhua River Basin.The SSP1-2.6 scenario promotes streamflow increase and drought mitigation,while the SSP2-4.5 and SSP5-8.5 scenarios may exacerbate drought risks.The findings provide decision-making support for regional water resource management and disaster prevention,recommending differentiated adaptation strategies tailored to specific climate scenarios. 展开更多
关键词 lower Songhua River Basin CMIP6 hydrological drought run theory SWAT model streamflow shared socioeconomic pathways influencing factors
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Lagged effects of risk factors on the disability of older adults:A distributed lag non-linear model approach 认领 引用 被引量：1
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作者 Yitong Mao Zhiting Guo +2 位作者 Wen Gao Yuping Zhang Jingfen Jin 《International Journal of Nursing Sciences》 CSCD 2026年第1期53-60,I0004,I0005,共8页
Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and ... Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and Retirement Longitudinal Study(CHARLS).After feature selection via Elastic Net Regularization,we applied DLNMs to evaluate the lagged effects of risk factors.Disability was defined as the presence of any difficulties in basic activities of daily living(BADL).The cumulative relative risk(CRR)was calculated by summing the lag-specific risk estimates,representing the cumulative disability risk over the specified lag period.Effect modifications and sensitivity analyses were also performed.Results This study included a total of 2,318 participants.Early-phase lag factors,such as the difficulty in stooping(CRR=3.58;95%CI:2.31-5.55;P<0.001)and walking(CRR=2.77;95%CI:1.39-5.55;P<0.001),exerted the strongest effects immediately upon occurrence.Mid-phase lag factors,such as arthritis(CRR=1.51;95%CI:1.10-2.06;P=0.001),showed a resurgence in disability risk within 2-3 years.Late-phase lag factors,including depressive symptoms(CRR=2.38;95%CI:1.30-4.35;P<0.001)and elevated systolic blood pressure(CRR=1.64;95%CI:1.06-2.79;P=0.02),exhibited significant long-term cumulative risks.Conversely,grip strength(CRR=0.80;95%CI:0.54-0.95;P=0.02)and social participation(CRR=0.89;95%CI:0.73-0.99;P=0.04)were significant protective factors.Conclusions The findings underscore the importance of tailored interventions that account for various lag characteristics of different factors to effectively mitigate disability risk.Future studies should explore the underlying biological and sociological mechanisms of these lagged effects,identify intervention strategies that target risk factors with different lagged patterns,and evaluate their effectiveness. 展开更多
关键词 Ageing Disability Distributed lag non-linear models Nusing Risk factors
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Constructing a predictive model for postpartum anxiety in patients with preeclampsia based on multidimensional indicators and its application 认领 引用 被引量：1
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作者 Xiao-Yan Zhang Yun Shi +3 位作者 Yi-Ting Lu Ya-Jun Zhong Jia-Xian Wu Xiao-Qing Wang 《World Journal of Psychiatry》 SCIE 2026年第3期264-273,共10页
BACKGROUND Preeclampsia(PE)substantially increases the risk of postpartum anxiety,yet limited research has examined how disease onset and clinical features,such as blood pressure control and body mass index(BMI)change... BACKGROUND Preeclampsia(PE)substantially increases the risk of postpartum anxiety,yet limited research has examined how disease onset and clinical features,such as blood pressure control and body mass index(BMI)changes during pregnancy,affect this risk.AIM To develop and apply a predictive model for postpartum anxiety disorder in patients with PE based on multidimensional indicators.METHODS A cross-sectional study was conducted among 196 patients with PE admitted to the Department of Obstetrics,Ninth People’s Hospital of Suzhou(Affiliated with Soochow University),from June 2019 to June 2024.According to the self-rating anxiety scale at six weeks postpartum,participants were divided into anxiety and no-anxiety groups.Two data sets were analyzed,and multivariate logistic regression was performed to identify risk and protective factors.Regression coefficients and constants were used to construct the predictive model.Model performance was evaluated using the receiver operating characteristic curve and area under the curve,along with a goodness-of-fit test.The model was then validated with clinical data.RESULTS Of the 196 patients with PE evaluated using the self-rating anxiety scale at six weeks postpartum,51(26.02%)patients showed anxiety symptoms.Significant group differences(P<0.05)were observed for blood pressure control,BMI increase,hematocrit(Hct),family relationships,and psychological resilience.Logistic regression indicated that,poor blood pressure control,greater BMI increase,elevated Hct levels,and strained family relationships during pregnancy were risk factors for postpartum anxiety in patients with PE(P<0.05),whereas higher psychological resilience was a protective factor(P<0.05).The prediction model was defined as:Logit(P)=0.684×pregnancy blood pressure control+0.805×pregnancy BMI increase+0.756×Hct+1.063×family relationship-1.105×psychological resilience score-5.487.The model’s area under the curve(0.908)exceeded that of individual indicators:Blood pressure control(0.794),BMI increase(0.814),Hct(0.808),family relationships(0.840),and psychological resilience(0.833).The goodness-of-fit test showed no overfitting(χ2=1.904,P=0.725).Clinical validation demonstrated sensitivity of 85.71%,specificity of 87.72%,and accuracy of 87.18%.CONCLUSION Postpartum anxiety risk in patients with PE is associated with poor blood pressure control,excessive BMI gain,elevated Hct index,and poor family relationships,while strong psychological resilience serve as a protective factor.The developed prediction model effectively supports clinical assessment and targeted management of postpartum anxiety in patients with PE. 展开更多
关键词 Preeclampsia Postpartum Anxiety disorder Influencing factors Prediction model
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基于PMF模型的宁波市某工业区土壤重金属源解析及健康风险评价 认领 引用 被引量：3
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作者 王彦佳 刁春燕 李剑峰 《农业环境科学学报》 CAS CSCD 北大核心 2026年第2期424-433,共10页
为探究宁波市某工业区土壤重金属污染及人体健康风险情况,本研究以浙江省宁波市某工业区表层土壤为对象,系统分析了Cr、Cu、As、Cd、Pb、Ni、Sb、Hg等8种重金属的污染水平及其空间分布格局,采用地累积指数法评估其污染风险,并运用正定... 为探究宁波市某工业区土壤重金属污染及人体健康风险情况,本研究以浙江省宁波市某工业区表层土壤为对象,系统分析了Cr、Cu、As、Cd、Pb、Ni、Sb、Hg等8种重金属的污染水平及其空间分布格局,采用地累积指数法评估其污染风险,并运用正定矩阵因子分解模型(PMF)解析污染来源,通过健康风险评价模型量化重金属对人体的暴露风险。结果表明,Cu、As、Cd的平均含量达到地区土壤背景值的2.1、1.9、1.8倍。土壤Cr、Cu、Ni、Cd、As、Pb之间的相关系数介于0.24~0.59(P<0.01),6种元素之间均存在正相关关系,Cd、As、Cu 3种重金属元素之间存在显著相关性。地累积指数评价结果显示,各元素在研究区表层土壤中均出现不同程度的累积,其中Pb出现了中度污染情况,Hg和Cr元素在该研究区域内整体呈现出无污染或轻微污染,并未出现明显富集现象。源解析结果表明,Ni、Cr主要来源于自然源,Pb主要来源于交通排放源,Cu、Cd、As主要来源于农业源,Sb主要来源于工业制造源,Hg主要来源于工业及煤炭燃烧复合源。经口摄入是人群主要健康风险途径,且儿童的健康风险大于成人;不同年龄段人群经多种途径暴露于土壤中重金属的非致癌和致癌健康风险大部分处于可接受水平,但Cr、Cu、As、Pb、Ni存在一定的健康风险,因此这几种重金属的来源和污染情况必须引起关注。 展开更多
关键词 重金属 来源解析 健康风险评价 PMF模型 污染特征
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基于蒙特卡洛的水质综合评价及PMF溯源解析——以木兰溪为例 认领 引用 被引量：1
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作者 李光悦 陈锦 +4 位作者 刘继辉 石成春 李莉 李家兵 谢蓉蓉 《天津师范大学学报（自然科学版）》 CAS 北大核心 2026年第2期26-34,共9页
为了提高水环境评价及污染溯源的准确性和可靠性,基于2015—2019年木兰溪水质监测数据,采用蒙特卡洛模拟方法计算综合污染指数(H),通过相关性及敏感性分析识别综合污染指数的影响要素,最后采用正定矩阵因子分解法(positive matrix facto... 为了提高水环境评价及污染溯源的准确性和可靠性,基于2015—2019年木兰溪水质监测数据,采用蒙特卡洛模拟方法计算综合污染指数(H),通过相关性及敏感性分析识别综合污染指数的影响要素,最后采用正定矩阵因子分解法(positive matrix factor,PMF)进行污染溯源.结果表明:①时间上,2015—2019年研究区H值范围为0.67~0.81,除2017年和2018年小幅波动外,水质总体呈好转趋势;空间上,水质从上游到下游总体表现为明显恶化,受土地利用类型影响,中游P4和P5断面局部好转.②相关性分析表明,上游P3断面在污染程度严重的2015年和2018年对区域的H值影响最大,而下游P6断面在污染程度相对低的2016年、2017年和2019年对区域H值影响最大;敏感性分析表明,TN为研究区综合污染指数的主要影响指标.③PMF溯源结果表明,研究区汛期污染源贡献率排序为农业污染(33.5%)>生活与工业废水(31.0%)>有机污染源(21.2%)>季节效应(14.3%),非汛期污染源贡献率排序为农业污染(25.0%)>生活污水(22.0%)>季节效应(20.3%)>有机污染源(18.1%)>工业点源(14.6%). 展开更多
关键词 木兰溪 蒙特卡洛模拟 水质综合评价 综合污染指数 正定矩阵因子分解模型
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基于PMF和蒙特卡罗模拟的冶炼厂地块土壤重金属污染评估及源解析 认领 引用 被引量：1
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作者 闵康婷 杨国栋 +2 位作者 罗思雅 袁世杰 陈浪 《有色金属（中英文）》 CAS 北大核心 2026年第1期163-176,共14页
运用正定矩阵因子分解(PMF)受体模型和蒙特卡罗模拟,评估某冶炼厂遗留地块土壤重金属污染与健康风险。结果表明,土壤中As、Cu、Pb、Ni和Zn含量分别为湖北省土壤背景值的4.6、179.6、45.31、8.6和38.9倍,地累积指数判定为轻度污染;生态... 运用正定矩阵因子分解(PMF)受体模型和蒙特卡罗模拟,评估某冶炼厂遗留地块土壤重金属污染与健康风险。结果表明,土壤中As、Cu、Pb、Ni和Zn含量分别为湖北省土壤背景值的4.6、179.6、45.31、8.6和38.9倍,地累积指数判定为轻度污染;生态风险评估表明,89%的样点Cu、32%的样点As处于极强风险水平。PMF解析指出,工业源是主要污染来源(贡献率40%),自然源和混合源次之(分别为33%、27%)。健康风险评估(HRA)表明,成人和儿童致癌风险可接受,主要贡献元素为Ni;非致癌风险中,成人超阈值概率6.32%,儿童达49.5%,主要由Pb导致。根据土壤重金属污染来源和健康风险关系的分析结果,确定自然源有关的As为优先管控因子。参数敏感性分析显示,皮肤接触和口服摄入是成人与儿童主要接触途径,皮肤黏附系数和体重影响显著。两模型结合为土壤污染防控提供了精准依据。 展开更多
关键词 PMF模型 蒙特卡罗模拟 风险评估 来源解析 优先控制因子
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Modeling and prediction of monthly precipitation in Nanjing based on machine learning methods 认领 引用 被引量：1
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作者 PENG Niankui LU Xiaochun +2 位作者 HUA Cheng WANG Zhenqin DU Xin 《水利水电技术（中英文）》 CSCD 北大核心 2026年第5期82-93,共12页
[Objective]Accurate precipitation prediction plays a crucial role in regional flood prevention and mitigation,water resources management,and socioeconomic development.However,the precipitation process is influenced by... [Objective]Accurate precipitation prediction plays a crucial role in regional flood prevention and mitigation,water resources management,and socioeconomic development.However,the precipitation process is influenced by the interaction of multi-scale meteorological factors and shows significant nonlinearity and spatiotemporal heterogeneity.Traditional numerical models fail to effectively capture its complex evolution patterns.[Methods]Based on random forest stacking techniques,six hybrid prediction models were constructed:KNN-LSTM,SARIMA-KNN,SARIMA-Prophet,SARIMA-LSTM,Prophet-LSTM,and Prophet-KNN.Monthly precipitation data from 1990 to 2023 at station 58238 in Nanjing were used for modeling,with data from 1990 to 2020 used as the training set and data from 2021 to 2023 used as the testing set.The regional generalization ability was validated using contemporaneous data from 12 independent meteorological stations in Jiangsu Province.[Results]The result showed that the SARIMA-LSTM hybrid model,which integrated the seasonal decomposition advantage of SARIMA with the long-term dependency capturing ability of LSTM,achieved the highest prediction accuracy on the testing set,with R2=0.904,MAE=16.16 mm,and MSE=477.87 mm2.The regional generalization validation demonstrated that the model achieved R2=0.919,MAE=15.33 mm,and MSE=537.52 mm2 across 13 meteorological stations in Jiangsu Province,indicating good spatial generalization capability.[Conclusion]The constructed hybrid models exhibit excellent predictive performance,providing reliable technical support for precipitation prediction in the lower Yangtze River region.This holds significant application value for the optimization of regional water resource allocation and disaster early warning. 展开更多
关键词 precipitation prediction machine learning hybrid models SARIMA-LSTM regional generalization monthly precipitation random forest stacking influencing factors
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