沁水煤田15号煤中氟的赋存状态及其沉积环境分析

氟是煤中有害元素之一,燃煤型氟排放造成的污染已经对人类的健康安全构成威胁。研究煤中氟赋存状态及其沉积环境,对掌握高氟煤分布规律及控制燃煤造成的氟排放具有重要意义。通过对沁水煤田内6座煤矿15号煤样品的分析发现:煤中氟含量与灰分显著相关,与黄铁矿硫、有机硫无相关关系,表明煤中氟主要以无机物形式赋存,且与含硫矿物无关;与钾、镁、硅、铝等元素含量具有显著的相关关系,表明氟有可能的主要赋存形式为金云母、氟金云母等矿物,以及以吸附存在于高岭石、勃姆石、伊蒙混层等黏土矿物中;与钙、磷元素含量无显著相关性,表明氟不以氟磷灰石、含氟羟基磷灰石等矿物大量赋存。此外,通过对沁水煤田15号煤的沉积环境分析发现,弱还原环境、较低盐度、偏酸性、较强的水动力条件有利于该区域煤中氟的富集。     

Homogeneity and mechanical behaviors of sands improved by a temperature-controlled one-phase MICP method

Acta Geotechnica - Microbially induced carbonate precipitation (MICP) has been actively investigated as a promising method to improve soil properties. A burning issue impeding its wide application...     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

Basal stability analysis of braced excavations in anisotropic and non-homogeneous undrained clay using streamline velocity fields

Acta Geotechnica - A basal heave stability analysis in anisotropic and non-homogeneous undrained clay by using the kinematic approach of limit analysis is presented. The proposed failure mechanism...     

搬迁农户生计策略与土地利用行为耦合协调度分析--以贵州省习水县为例

易地扶贫搬迁改变了搬迁农户生计策略,同时影响了其土地利用行为,二者之间的耦合协调度直接影响着农户的可持续生计。本文以贵州省习水县易地搬迁农户调研数据为基础,构建以农户生计策略和土地利用行为为子系统的耦合协调度模型,分析2个子系统之间的耦合关系和耦合协调关系。研究表明:纯农型农户、农兼型农户、兼农型农户生计策略与土地利用行为之间的耦合度值介于0.4~0.5之间,水平较低,处于拮抗状态;不同类型农户生计策略与土地利用行为系统耦合协调度值均处于0.39~0.49之间,处于濒临失调阶段,存在较大优化空间;传统的农业生产形式对于改善农户生计无明显效果,引导农户向专业农业型农户转变对于促进移民安置区“人地系统”协调发展大有裨益。研究结果可为农户生计与土地利用的可持续发展提供理论依据。     

生态地质研究进展与展望

生态地质学是研究生态系统与地质环境之间关系的一门交叉学科,对国土空间生态保护修复工作有重要理论支撑作用。我国生态地质研究工作虽然经过了多年的发展与积淀,但时至今日生态地质学仍然处于研究和探索阶段。鉴于此,基于前人的大量研究,总结了国内外生态地质研究进展: 国际上,俄罗斯建立了生态地质学研究体系,美国发起的地球关键带研究是与生态地质研究十分契合的主题; 在国内,生态地质研究主要着眼于”生态-地质”相互作用过程与机理以及地质环境影响下的系统性生态修复研究。在此基础上,提出了生态地质学涵义及其研究内容、方法技术创新及学科体系构建思路,以期为服务山水林田湖草沙整体保护、系统修复、综合治理和生态地质系统深化研究提供借鉴。     

中国冰冻圈变化的适应研究：进展与展望

冰冻圈变化的适应研究是冰冻圈科学领域的新兴研究方向,是当今自然科学与社会科学交叉融合跨学科集成研究的典型代表。起步于2007年的中国冰冻圈变化适应研究,经历了早期的探索,研究重点由评价脆弱性发展为量化冰冻圈变化的影响,形成以影响/风险—脆弱性—适应全链条的完善的研究体系,研究方法突破传统的指标体系赋权法的不足,初步实现了定量化,有机结合影响/风险、脆弱性、适应三方面的研究结果,使冰冻圈变化的适应措施由偏重宏观性、普适性开始转向更有针对性。未来中国冰冻圈变化的适应研究应拓展、完善和深化现有的理论体系,构建冰冻圈与社会经济耦合模型,科学量化冰冻圈全要素变化的影响,建立不同利益相关者与科学家共同参与的研究新模式,科学有效应对与适应冰冻圈变化及其影响。     

鄂尔多斯盆地CO2地质封存适宜性与潜力评价

针对目前利用层次分析法对CO₂地质封存进行适宜性评价过程中,极少结合研究区域实际计算低层次评价指标权重,对适宜性评价结果又缺少进一步的分析,结合鄂尔多斯盆地的地质特征,通过计算指标组成权重和适宜性得分对盆地开展了CO₂地质封存适宜性评价,并以适宜区杏子川油田长4+5盖层为例,开展了盖层封闭性评价实验研究。同时,采用相应的计算方法对鄂尔多斯盆地深部咸水层和油藏的CO₂地质封存潜力进行了计算。结果表明：鄂尔多斯盆地在三叠系开展CO₂地质封存的适宜性最好,石炭-二叠系和奥陶系则次之;杏子川油田三叠系延长组长4+5盖层对区域开展CO₂地质封存具备良好的封闭性;鄂尔多斯盆地深部咸水层和油藏的CO₂有效封存量分别为1.33×10 ¹⁰ t和1.91×10 ⁹ t,且在延长石油吴起、靖边及杏子川油田共有56个CO₂地质封存适宜区,其CO₂有效封存量可达1.77×10 ⁸ t。     

海南岛天然橡胶林台风灾害风险评价

台风灾害是海南橡胶种植中影响最为严重和主要的灾害,为对其风险进行定量评估,本研究以海南岛天然橡胶林为研究对象,基于灾害风险评估理论,融合橡胶台风灾害、社会经济和气象数据,建立橡胶台风灾害危险性、暴露性和脆弱性评价模型,利用加权综合评价法开展天然橡胶林台风灾害风险评价。结果表明：海南橡胶种植高风险区位于沿海台风发生频繁市县,其中琼海、文昌、海口为海南岛橡胶灾害风险最高的地区,其次陵水、万宁、琼中、屯昌、东方等地区灾害风险也较高。风险最低地区位于中部五指山、保亭、乐东、三亚等地区,评价结果与实际灾害发生以及种植情况相符。评价结果表明,台风灾害危险性是风险的主导因子,但非单一决定因子,种植技术、品种改良等措施对脆弱性降低起到了较好的促进作用。评价结果可为橡胶林避灾防灾及种植布局提供依据。