铜陵地区老鸦岭层状钼矿床铅同位素组成研究

安徽铜陵老鸦岭矿床中二叠系大隆组(P2d)顶部的含矿(钼矿化)黑色页岩以及附近(立新煤矿)同一层位不含矿黑色页岩的实测铅同位素组成分别为：^206Pb/^204Pb20.20～22.37,^207Pb/^204Pb15.67～15.82,^208Pb/^204Pb38.47～38.60和^206Pb/204Pb18.83～20.80,^207Pb/^204Pb15.65～15.76,^208Pb/^204Pb38．84～39．22。对137Ma的放射成因Pb进行校正后的铅同位素组成表明，含矿黑色页岩和不含矿黑色页岩均与燕山晚期火成岩无关，老鸦岭含矿黑色页岩可能具沉积成因。对沉积(约250Ma)以来的放射成因Pb进行校正后的铅同位素组成表明：不含矿黑色页岩的Pb源自上地壳，而含矿黑色页岩的Pb(因而推测其他成矿金属)可能源于上地壳物质(与不含矿黑色页岩的Pb源相似)与下地壳物质的混合。     

鄂尔多斯盆地中生代晚期以来大地热流的变化及其对生态环境格局和演变的影响

鄂尔多斯盆地的西北部、东北部和南部三个区域现今大地热流平均值分别为56．3、67．3和65．3mW／m^2，对应的生态环境格局也有明显的差异。研究表明，大地热流每增加4～5mW／m^2可使年均地表温度升高约l℃，使最低月均地表温度升高2。C以上。鄂尔多斯盆地东北部的平均大地热流比西北部高出11mW／m^2，东北部年均地表温度可能比西北部高出2～3℃，其最低月均地表温度可能比西北部高出4～6℃。西北部的大地热流平均值已经低于维持地表生态系统延续所需大地热流的临界值(57mW／m^2)，其自然生态系统整体上已经处于脆弱境地；东北部和南部的大地热流均大于57mW／m^2，自然生态系统均尚较稳健。东北部的沙漠化可能是风沙侵入的结果，其生态应该是可以恢复的。整个西北部作为一个整体看，72万年以前大地热流就已衰减到临界值以下，区域生态系统渐趋脆弱，开始整体上向荒漠化演变。     

Study of statistically correcting model CMAQ-MOS for forecasting regional air quality

Based on analysis of the air pollution observational data at 8 observation sites in Beijing including outer suburbs during the period from September 2004 to March 2005, this paper reveals synchronal and in-phase characteristics in the spatial and temporal variation of air pollutants on a city-proper scale at deferent sites; describes seasonal differences of the pollutant emission influence between the heating and non-heating periods, also significantly local differences of the pollutant emission influence between the urban district and outer suburbs, i.e. the spatial and temporal distribution of air pollutant is closely related with that of the pollutant emission intensity. This study shows that due to complexity of the spatial and temporal distribution of pollution emission sources, the new generation Community Multi-scale Air Quality (CMAQ) model developed by the EPA of USA produced forecasts, as other models did, with a systematic error of significantly lower than observations, albeit the model has better capability than previous models had in predicting the spatial distribution and variation tendency of multi-sort pollutants. The reason might be that the CMAQ adopts average amount of pollutant emission inventory, so that the model is difficult to objectively and finely describe the distribution and variation of pollution emission sources intensity on different spatial and temporal scales in the areas, in which the pollution is to be forecast. In order to correct the systematic prediction error resulting from the average pollutant emission inventory in CMAQ, this study proposes a new way of combining dynamics and statistics and establishes a statistically correcting model CMAQ-MOS for forecasts of regional air quality by utilizing the relationship of CMAQ outputs with corresponding observations, and tests the forecast capability. The investigation of experiments presents that CMAQ-MOS reduces the systematic errors of CMAQ because of the uncertainty of pollution emission inventory and improves the forecast level of air quality. Also this work employed a way of combining point and area forecasting, i.e. taking the products of CMAQ for a center site to forecast air pollution for other sites in vicinity with the scheme of model products "reanalysis" and average over the "area".     

Characterization and Application of S-Band Polarimetric Radar and X-Band Phased Array Radar for a Tornadic Storm Event on June 16,2022

The X-band phased array radar offers faster scanning speed and higher spatial resolution compared to the S-band radar, making it capable of enhancing tornado monitoring and early warning capabilities. This study analyzed the char- acteristics and nowcasting signals of a tornado case that occurred on June 16, 2022 in the Guangzhou region. Our findings indicate that the violent contraction of rotation radius and the dramatic increase in rotation speed were important signal characteristics associated with tornado formation. The X-band phased array radar, with its high temporal and spatial resolution, provided an opportunity to capture early warning signals from polarimetric characteristics. The X-band phased array radar demonstrated noteworthy ability to identify apparent tornado vortex signature (TVS) features in a 10-minute lead time, surpassing the capabilities of the CINRAD/SA radar. Additionally, due to its higher scanning frequency, the X- band phased-array radar was capable of consistently identifying TVS with shorter intervals, enabling a more precise tracking of the tornado’s path. The application of professional radars, in this case, provides valuable insights for the monitoring of evolutions of severe local storms and even tornadoes and the issuance of early warning signals.     

葛洲坝至胭脂坝长江干流段江豚活动规律

长江江豚是我国一级保护野生动物,也是长江生态系统的指示性物种,其种群数量恢复情况及活动规律一直备受关注。本文选择长江宜昌段江豚活动频繁的葛洲坝下游至胭脂坝江段为研究区域,于2021年6月-2022年5月采用定点目测、水上流动监测与无人机监测相结合的方法分区监测长江江豚的游泳行为,分析长江江豚的活动规律,构建了长江江豚出水头次的零膨胀泊松回归模型,识别影响长江江豚出水头次的关键因素,建立长江江豚出水头次与各因素间的相关关系。结果表明:(1)葛洲坝至胭脂坝长江干流段监测到最大江豚出水头次为19头次,长江江豚集群规模以2~3头最为常见,占比达58.1%;长江江豚主要表现出4种行为特征,各行为占比从大到小依次为:玩耍＞休息＞摄食＞抚幼。(2)长江江豚在葛洲坝下游近坝区(A区,葛洲坝至至喜长江大桥)出水头次最多,且在秋冬季节累计出水头次多于春夏季节,冬季累计出水头次最高,达252头次。(3)长江江豚出水头次与电站下泄流量呈显著负相关;浊度增大,长江江豚出水的概率减小。本文研究结果对长江江豚生态保护策略及长江十年禁渔效果评估具有重要参考价值。     

The solubility of quartz in aqueous sodium chloride solution at 350°C and 180 to 500 bars

The solubility of quartz in 2, 3, and 4 molal NaCl was measured at 350°C and pressures ranging from 180 to 500 bars. The molal solubility in each of the salt solutions is greater than that in pure water throughout the measured pressure range, with the ratio of solubility in NaCl solution to solubility in pure water decreasing as pressure is increased. The measured solubilities are significantly higher than solubilities calculated using a simple model in which the water activity in NaCl solutions decreases either in proportion to decreasing vapor pressure of the solution as salinity is increased or in proportion to decreasing mole fraction of water in the solvent.     

A 3D multi-threshold,region-growing algorithm for identifying dust storm features from model simulations

Dust storms cause significant damage to health, property, and the environment worldwide every year. To help mitigate the damage, dust forecast models simulate and predict upcoming dust events, providing valuable information to scientists, decision makers, and the public. These simulation outputs are in four-dimensions (i.e., latitude, longitude, elevation, and time) and represent spatially heterogeneous dust storm features and their evolution over space and time. This research investigates and proposes an automatic multi-threshold, region-growing-based algorithm to identify critical dust storm features from 3D dust storm simulations. A multi-threshold scheme is defined for the identification of dust storm features with different dust concentrations. Based on the multi-thresholds, dust storm features are iteratively identified by developing a region-growing algorithm that splits a clustered dust storm feature into multiple sub-features. The proposed approach is compared with three commonly used methods in image processing and thunderstorm identification. The proposed approach outperforms the other three methods in sensitivity and quantitative/qualitative accuracy. This research approach may also be slightly adjusted to identify critical 3D features from simulation outputs for other severe weather and geographical phenomena.