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...     

Boreal Summer Intraseasonal Oscillation in the Asian–Pacific Monsoon Region Simulated in CAMS-CSM

The boreal summer intraseasonal oscillation(BSISO) is simulated by the Climate System Model(CSM) developed at the Chinese Academy of Meteorological Sciences(CAMS), China Meteorological Administration. Firstly, the results indicate that this new model is able to reasonably simulate the annual cycle and seasonal mean of the precipitation, as well as the vertical shear of large-scale zonal wind in the tropics. The model also reproduces the eastward and northward propagating oscillation signals similar to those found in observations. The simulation of BSISO is generally in agreement with the observations in terms of variance center, periodicity, and propagation, with the exception that the magnitude of BSISO anomalous convections are underestimated during both its eastward propagation along the equator and its northward propagation over the Asian–Pacific summer monsoon region. Our preliminary evaluation of the simulated BSISO by CAMS-CSM suggests that this new model has the capability, to a certain extent, to capture the BSISO features, including its propagation zonally along the equator and meridionally over the Asian monsoon region.     

An Assessment of ENSO Stability in CAMS Climate System Model Simulations

We present an overview of the El Ni?o–Southern Oscillation(ENSO) stability simulation using the Chinese Academy of Meteorological Sciences climate system model(CAMS-CSM). The ENSO stability was quantified based on the Bjerknes(BJ) stability index. Generally speaking, CAMS-CSM has the capacity of reasonably representing the BJ index and ENSO-related air–sea feedback processes. The major simulation biases exist in the underestimated thermodynamic damping and thermocline feedbacks. Further diagnostic analysis reveals that the underestimated thermodynamic feedback is due to the underestimation of the shortwave radiation feedback, which arises from the cold bias in mean sea surface temperature(SST) over central–eastern equatorial Pacific(CEEP). The underestimated thermocline feedback is attributed to the weakened mean upwelling and weakened wind–SST feedback(μ_a) in the model simulation compared to observation. We found that the weakened μ_a is also due to the cold mean SST over the CEEP.The study highlights the essential role of reasonably representing the climatological mean state in ENSO simulations.     

CMIP5多模式集合对江苏省气候变化模拟评估及情景预估

利用中国气象局所属的2 400余个台站观测资料制作的分辨率为0.25°×0.25°数据集中的气温、降水量资料评估了CMIP5中17个模式对于1961—2004年江苏省气温和降水量空间分布特征的模拟能力,筛选出了5个对江苏省气候特征模拟较好的模式。之后基于5个优选模式集合平均的结果预估了3种典型浓度路径(Representative Concentration Pathways,RCPs)下江苏省2006—2100年的气温和降水量变化趋势。结果表明:(1)全球耦合气候模式对江苏省的气温和降水量空间分布特征具有一定的模拟能力,并且模式集合平均的气温和降水量与观测资料的空间相关系数分别为0.85和0.93;(2)在低浓度路径(RCP2.6)、中浓度路径(RCP4.5)和高浓度路径(RCP8.5)3种温室气体排放情景下,江苏省2006—2100年的地表温度均呈现明显的增温趋势,并且苏北的增温幅度要高于苏南;(3)3种温室气体排放情景下,江苏省未来百年降水量均呈现出北方增多南方减少的趋势;(4)未来百年江苏省降水量随气温变化的趋势并不稳定,RCP2.6和RCP4.5情景下降水量随气温的升高而增加,而RCP8.5情景下降水量随气温的增加而减少。     

北京山区与平原冬季近地面风的精细观测特征

利用2009—2018年冬季北京地区200多个自动气象站逐时10 m风速、风向观测数据,分典型区域（山区、山区与平原过渡区、平原区、城区）研究北京地区冬季近地面风的精细特征,并使用有完整记录的2 a（2017和2018年）冬季延庆高山区不同海拔高度10 m风逐时观测数据,多视角分析高山区不同海拔高度近地面风的特征和成因,以深刻认识北京地区复杂地形条件下冬季近地面风的特征和规律。结果表明:（1）北京地区冬季近地面平均风受西部北部地形、城市下垫面粗糙度和冷空气活动共同影响,平均风速沿地形梯度分布,山区高平原低,平原中又以城区风速最小;盛行西北风和北风,在城区东、西两侧盛行风出现扰流,在山区和过渡区一些地方还存在与局地地形环境明显关联的其他盛行风向。（2）4个典型区域冬季近地面风速日变化均表现为白天风速大于夜间,午间风速最大的“峰强谷平”单峰特征,这一特征的稳定性在城区高、山区低。（3）4个区域冬季弱风（< 1 m/s）频率为31%—42%,城区较高、山区较低;强风（> 10.8 m/s）频次则是山区多、城区少,强风风向主要表现为偏西—偏北,与冷空气活动密切关联;城区、平原区和过渡区偏南风频率均为极小,暗示北京“山区—平原”风模态在冬季是“隐式”的、不易被直接观测到。（4）近地面风的水平尺度代表范围在延庆高山区高海拔处明显大于低海拔处,海拔1500 m附近（平均的边界层顶高度）是延庆高山近地面风速日变化特征的“分水岭”,低于该海拔高度时近地面风速日变化表现为前述“峰强谷平”单峰特征,而高于该海拔高度时近地面风速日变化则呈现相反特征,即夜间大白天小、午间最小的“峰平谷深”特征,这是由边界层湍流活动的日变化及伴随的低层自由大气动量向边界层内下传所致。（5）延庆高山近地面风速大体上随观测高度而增大,高海拔站点日平均风速数倍于低海拔站点。白天—前半夜,海拔约2000 m的站点冬季盛行偏西风,风向变化不大,但风速为2—12 m/s;1000 m左右的低海拔站则风速比较稳定（< 6 m/s）,风向从午间至傍晚相对多变。      

利用风廓线雷达研究郑州机场低空急流特征及其对飞行的影响

利用2016、2017年郑州机场高分辨率边界层风廓线雷达半小时平均观测资料, 对机场上空低空急流时空分布特征进行统计研究, 结果表明:夏末、秋季低空急流出现次数相对较少, 春季、夏初是高发时期, 冬季易出现较强的超低空急流, 只有春季风速从低层到高层呈现先增大后减小、再增大的变化过程, 8月末可能是急流的时空转换期; 夜间和凌晨是高发时段, 白天降低30%~40%, 一般情况下, 00—12时(世界时, 下同)急流较弱, 12时后明显增强向上发展, 19时开始减弱, 持续至21时; 急流中心最大风速一半以上在12~18 m/s, 高度集中在60~180 m和300~900 m, 超低空急流占大部分, 夜间出现最大风速的概率远高于白天; 低空急流发生高度大部分在飞机起飞或着陆的范围内, 使飞机复飞概率增加, 对夜间航班影响更大。