基于模糊聚类关联分析法的煤与瓦斯突出程度分析

运用模糊聚类分析方法对煤与瓦斯突出的样本集合进行分类,建立了不同突出程度的模糊模式.用关联分析确定待分析样本与模式的关联程度,以此预测预报样本的煤与瓦斯突出危险程度.实例分析表明,与模糊聚类分类后、将模式与待预报样本组成新样本集合进行聚类分析并以此分类结果进行预报的方法相比,这种预报方法不仅可靠程度高,而且能定量描述待报样本与模式的亲和程度.     

河岸带地下水营养元素和有机质变化及与洪水的响应关系研究

河岸带地下水和河水存在复杂的交互作用,地下水和地表水存在明显的补排关系,洪水事件是影响河岸带地下水水质波动的重要水文过程. 以黄河湿地国家级自然保护区孟津湿地为研究对象,通过河岸带地下水营养元素指标(特别是小浪底水库调水调沙期间)野外定位观测,深入分析了河岸带地下水水质变化及其与洪水的响应关系. 结果表明,河岸滩区的农业开发存在明显的氮、磷下渗流失风险. 临近河岸的农耕旱作区,是河流与人工湿地之间一个特殊的氮污染物控制单元,对地下水和河流之间的氮迁移隔离起着极为重要的作用. 在人工湿地,农家粪作为底肥加入可能是磷下渗流失的重要源头,进入地下水中的磷顺着水力坡度还发生着显著的横向迁移,尤其在调水期横向迁移更加明显. 河岸滩区的开发类型及其耕作制度对地下水的硝氮含量产生重要的影响. 在鱼塘区,常年的土壤厌氧环境加重了氮的下渗迁移和积累;在荷塘区,春夏季节,土壤淹没呈厌氧环境,氮迁移和硝化作用显著,在秋冬季节,土壤呈好氧环境,氮硝化作用显著发生,全年氮达到相对平衡的状态;距离河岸50～200 m之间氮的硝化-反硝化作用强烈,是一个高效的微生物氮净化单元. 人工湿地施用的农家粪是有机物流失的重要源头,河岸滩区土壤质地呈沙性,渗透能力强,土壤保水保肥能力差,在此区进行农业活动,尤其是人工湿地开发中大量施用肥料,容易造成土壤表层有机质和氮磷养分因灌溉而导致的下渗流失,进而污染地下水与河水,较由降雨引起的地表径流流失显得更为突出. 距离河道50～200 m的范围是重要的污染净化单元,为典型的滩区地下水-河流的水陆交错带. 该区域的合理保护,对于保护河流水质和地下水水质十分重要.     

羟基多溴联苯醚对鲤鱼急性毒性及定量结构活性关系

羟基多溴联苯醚是一类具有环境风险的新兴污染物,它们已经在众多环境介质甚至人体内广泛存在。参照GB/T13267-91标准方法,采用静态生物急性毒性试验,测定了6种羟基多溴联苯醚(2′-OH-BDE7、4′-OH-BDE17、2′-OH-BDE28、2′-OH-BDE68、4′-OH-BDE90和2′-OH-BDE123)对普通鲤鱼的急性毒性96 h-LC50值,分别为697、1 130、854、550、644和522 ng.mL-1。除4′-OH-BDE17为高毒物质外,其他5种OH-PBDEs均为剧毒物质,高溴代的2′-OH-BDE123毒性最大。选用OH-PBDEs的KOW参数及由MOPAC软件PM3算法计算出的16个量子化学参数(EHomo、qBr+、ELumo等)为描述符,运用一元线性回归分析分别研究了96 h-LC50与他们之间的相关关系。结果表明:lgKOW和ELumo与6种羟基多溴联苯醚的96 h-lg LC50表现出较好的相关性,复相关系数均大于0.96,根据方程得到的96 h-lg LC50预测值与实验值基本相同,进一步对环境中广泛检出的其它OH-PBDEs的96 h-LC50值也进行了预测。     

偶氮类染料脱色率的定量构效关系

偶氮类染料的生产和使用过程中存在着三废多、难脱色和污染严重等问题,该染料是印染工业的主要污染物。选取偶氮类染料的分子结构参数和其光催化氧化脱色率之间建立定量结构活性关系(QSAR),进而得到回归方程,为印染废水处理和染料环境行为评价提供理论预测。结果表明,偶氮类染料的光催化氧化脱色率与其结构之间存在着线性相关性,线性方程为:D=0.647μ+66.277,(D为脱色率、μ为偶极矩)R=0.989方程具有预测能力。     

Property-performance relationship of core-shell structured black TiO2 photocatalyst for environmental remediation

● Properties and performance relationship of CSBT photocatalyst were investigated. ● Properties of CSBT were controlled by simply manipulating glycerol content. ● Performance was linked to semiconducting and physicochemical properties. ● CSBT (W:G ratio 9:1) had better performance with lower energy consumption. ● Phenols were reduced by 48.30% at a cost of $2.4127 per unit volume of effluent. Understanding the relationship between the properties and performance of black titanium dioxide with core-shell structure (CSBT) for environmental remediation is crucial for improving its prospects in practical applications. In this study, CSBT was synthesized using a glycerol-assisted sol-gel approach. The effect of different water-to-glycerol ratios (W:G = 1:0, 9:1, 2:1, and 1:1) on the semiconducting and physicochemical properties of CSBT was investigated. The effectiveness of CSBT in removing phenolic compounds (PHCs) from real agro-industrial wastewater was studied. The CSBT synthesized with a W:G ratio of 9:1 has optimized properties for enhanced removal of PHCs. It has a distinct core-shell structure and an appropriate amount of Ti³⁺ cations (11.18%), which play a crucial role in enhancing the performance of CSBT. When exposed to visible light, the CSBT performed better: 48.30% of PHCs were removed after 180 min, compared to only 21.95% for TiO₂ without core-shell structure. The CSBT consumed only 45.5235 kWh/m³ of electrical energy per order of magnitude and cost $2.4127 per unit volume of treated agro-industrial wastewater. Under the conditions tested, the CSBT demonstrated exceptional stability and reusability. The CSBT showed promising results in the treatment of phenols-containing agro-industrial wastewater.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

东洞庭湖湖滨带土壤酸碱度的分布及对重金属含量的影响

用统计学方法研究了东洞庭湖湖滨带土壤pH 值的分布特征及与重金属污染特征关系。研究表明：在东洞庭湖湖滨带67个采样点中,7.46％的土样为酸性土壤,多分布在居民地和旅游区;13.43％的土样为中性土壤,多分布在湿地保护区;79.10％的土壤为碱性土壤,主要分布在农业区和工业区;无强酸性和强碱性样品。不同土壤pH范围的重金属平均含量不同,随着土壤pH值由酸性、中性到碱性的升高,Hg、Cd、Pb、Zn含量先降低后增加;As、Cu、Ni、Cr含量先增加后降低。     

鄱阳湖沉积物可转化态氮分布特征及其对江湖关系变化的响应

选取不同高程鄱阳湖表层沉积物,通过研究其总可转化态氮与各形态可转化态氮含量及分布特征,试图揭示江湖关系变化导致的水位变化对鄱阳湖沉积物氮潜在释放风险的影响.结果表明:1鄱阳湖表层沉积物总氮(TN)含量在389~3 865 mg·kg-1之间,空间分布上呈"五河"入湖尾闾区湖心区北部湖区的趋势;总可交换态氮含量在319.36~904.56 mg·kg-1之间,占TN的52%,空间分布趋势与TN相同;2鄱阳湖3个湖区沉积物各形态可转化态氮的含量大小排列次序均为:SOEF-N(强氧化剂可提取态氮)≈SAEF-N(强碱可提取态氮)WAEF-N(弱酸可提取态氮)IEF-N(离子交换态氮);3江湖关系变化致使鄱阳湖枯水期沉积物出露时间提前并且延长,进而导致不同高程沉积物可转化态氮(TTN)含量差异明显,3个湖区沉积物可转化态氮含量均表现为枯水期丰水期,高程越高,由于其沉积物出露时间较长,可转化态氮含量较高,即可转化态氮含量12 m~13 m高程沉积物11 m~12 m高程沉积物10m~11 m高程沉积物;4随着高程的增加,沉积物各形态可转化态氮含量都呈现增加的趋势,其中SAEF-N和WAEFN含量及其占总可转化态氮的比例变化幅度较小,而IEF-N和SOEF-N含量以及其占总可转化态氮比例的增幅均较为显著.如果江湖关系进一步变化,枯水期水位继续下降,势必会引起沉积物出露面积增大及出露时间延长,从而导致沉积物TN、可转化态氮以及释放风险较高的氮形态IEF-N和SOEF-N含量的增大,来年丰水期可能会增加鄱阳湖沉积物氮释放风险.     

含疏松缺陷的ZL205A合金力学性能研究

目的获取含疏松缺陷ZL205A材料主要力学性能参数的变化规律及力学行为。方法通过单轴拉伸实验测试,采用割线法估算含不同等级疏松ZL205A试样的力学性能参数;基于试样断面及载荷-位移曲线分析,归纳ZL205A材料的力学行为,并通过有限元模拟对假设的力学模型进行验证。结果发现ZL205A材料的抗拉强度、伸长率、弹性模量及屈服强度指标呈现随疏松等级增加而降低的趋势,材料变形塑性屈服阶段不明显且具有脆性断裂特征。结论 Ramberg-Osgood方程适合于描述ZL205A材料的弹塑性本构关系。     

新常态下要科学认识环境管理六个量的关系

针对新常态下环境管理面临的机遇与挑战,本文提出了环境管理工作要树立新的思维,并在此基础上深入剖析了总量与质量、容量与流量、存量与增量的关系。现行的总量控制制度在实施过程中带来的污染减排潜力越来越小,因此,环境管理的目标应从以污染排放控制为主向以环境质量改善为主转变,通过采取具有针对性的差异化容量总量控制管理手段,实现污染排放流量管控,同时,应充分考虑现有环境本底负荷的问题,实现污染存量和可能增量的协同控制,这对于推进环境管理工作的战略转型具有借鉴意义。