微波消解-电感耦合等离子体质谱法测定海泡石中的稀土元素

海泡石是一种纤维状含水的富镁硅酸盐黏土矿,其中的稀土元素含量在1×10~(-7)～1×10~(-5)之间,目前还没有建立海泡石中稀土元素的国家标准分析方法。测定岩石中的稀土元素主要是采用电感耦合等离子体质谱法(ICP-MS),样品前处理一般采用封闭溶矿和碱熔,但这两种处理方法耗时较长,效率不高。本文通过比较硝酸-氢氟酸-过氧化氢、硝酸-氢氟酸、硝酸-过氧化氢三种样品前处理方法,确定使用硝酸-氢氟酸溶矿,然后进行微波消解同时赶去氢氟酸,避免氢氟酸与稀土元素生成难溶的氟化物,再采用ICP-MS法测定15种稀土元素的含量。由于海泡石中的镁含量较高,为降低基体效应,以~(103)Rh和~(185)Re作内标补偿基体效应和校正灵敏度漂移,各元素测定值的准确性显著提高,回收率为91. 2%～110. 9%,检出限为0. 002～0. 011μg/L,精密度≤2. 79%。本方法与封闭酸溶ICP-MS法的分析结果吻合较好,且用酸量少(7 mL),溶矿效率高(1 h),检出限更低。     

2000-2014年西藏雅鲁藏布江流域积雪时空变化分析及对气候的响应研究

利用2000-2014年MODIS逐日无云积雪产品对雅鲁藏布江流域积雪特征的空间分布及变化、积雪随高程变化的规律进行了分析,并采用被动微波数据SMMR （1979-1987年）和SSM/I （1988-2008年）以及中国地面降水和气温0.5°×0.5°日值格点数据集,研究了雅鲁藏布江流域关键积雪参数对气候要素的响应等。结果表明：流域下游积雪日较大且变化剧烈;流域整体上呈显著减少的趋势;积雪日随高程的上升而增加;流域内降水呈不显著的增加趋势,而气温呈显著的增加趋势,最高气温对积雪变化影响最大;气温对积雪终日的影响明显高于积雪初日;在积雪消融期降水的增多促进了积雪的消融。     

IPCC AR6报告解读：气候系统对太阳辐射干预响应

IPCC第六次评估报告（AR6）第一工作组报告评估了太阳辐射干预（Solar radiation modification,SRM）对气候系统和碳循环的影响。在大幅度减排基础上,太阳辐射干预有潜力作为应对气候变化的备用措施。目前,对于太阳辐射干预气候影响的评估都是基于模式模拟结果。评估主要结论如下：太阳辐射干预可以在全球和区域尺度上抵消一部分温室气体增加造成的气候变化（高信度);但是太阳辐射干预无法在全球和区域尺度上完全抵消温室气体增加引起的气候变化（几乎确定);有可能通过适当的太阳辐射干预设计,同时实现多个温度变化减缓目标（中等信度);在高强度温室气体排放情景下,如果太阳辐射干预实施后突然终止,并且这种终止长时间持续,将会造成快速的气候变化（高信度);如果在减排和CO₂移除的情况下,太阳辐射干预的实施强度逐渐减小至零,将显著降低太阳辐射干预突然终止产生的快速气候变化风险（中等信度);太阳辐射干预会通过降温作用,促进陆地和海洋对大气CO₂的吸收（中等信度),但是太阳辐射干预无法缓解海洋酸化（高信度);太阳辐射干预对其他生物化学循环影响的不确定性大。由于对云-气溶胶-辐射过程的相互作用和微物理过程认知有限,目前对平流层气溶胶注入、海洋低云亮化、高层卷云变薄等太阳辐射干预方法的冷却潜力和气候效应的认知还有很大的不确定性。     

微波辐射计在对流天气预报中的应用

选取2016—2018年每年4—9月份RPG-HATPRO型42通道微波辐射计观测的不稳定指数参数(K、SI、CAPE、LI)及水汽参数(IWV、LWP),研究得出各参数触发雷雨大风、短时强降水的阈值条件为K>37℃、SI<-1℃、IWV>60 kg/m~2、LWP>400 g/m~2,而LI、CAPE无法对3种天气类型进行区分。利用费舍判别分析方法,将不稳定指数参数及水汽参数作为预报因子,建立预报方程并进行检验,结果表明:二级判别方程预测对流天气的准确率为76%,可以作为预报对流天气的辅助工具;多级判别方程不能很好地区分3种天气类型,但将其作为修正后的二级判别方程使用,能提高对流天气的测中概率。     

微波等离子体原子发射光谱法测定偏远矿区海泡石中的主微量元素

海泡石是具有层状结构的含水富镁硅酸盐黏土矿物,其中无机元素含量是揭示其成矿物质来源、成矿流体性质和矿床成因的重要依据,通常采用电感耦合等离子体发射光谱/质谱法(ICP-OES/MS)进行测定,等离子体(ICP)的高温激发会产生成大量谱线干扰,维持ICP稳定工作需使用高纯氩气,持续供气对于偏远矿区海泡石的检测还将面对气体采购和运输不便的问题。本文基于微波等离子体原子发射光谱(MP-AES)的低温激发技术减少光谱干扰,建立了准确测定偏远矿区海泡石中主量元素Mg、Al、Ca、Fe、K、Na和微量元素Cu、Zn、Mn、Pb含量的分析方法。利用硝酸-盐酸-氢氟酸混合酸对海泡石进行微波消解,避免了样品处理过程中分析元素的损失,加快了样品处理速度,同时提高了样品溶液的稳定性。通过选择各元素光谱线的分析波长,并利用快速线性干扰校正(FLIC)技术校正光谱干扰,以Lu为内标元素校正基体效应,提高了灵敏度和准确度。各元素的检出限为0.19～14.6μg/L。海泡石国家标准物质(GBW07138)各元素测定值与认定值的相对误差在-5.0%～6.7%之间。本方法具有检出限低、线性范围宽、结果准确等优点;MP-AES采用自带的氮气发生器为等离子体提供氮气作为工作气,无需引入复杂气体,提高了分析效率,尤其适用于气体采购和运输不便的偏远矿区。     

松嫩盆地北部林甸地热田供暖尾水处理试验

将混入污染物和杂质的地热尾水直接排向地表水体,会造成水、土环境污染,也会造成水资源的浪费。为高效减少地热尾水中污染物,实现供暖地热尾水的无害化排放,以林甸县花园镇供暖地热尾水为例,通过混凝沉淀、超滤、纳滤工艺开展供暖尾水处理的室内实验和中试试验研究,连续监测获取地热尾水各处理工艺运行参数,组合工艺稳定运行期间监测到溶解性总固体浓度由5 824.7 mg/L降为432.40 mg/L、氯化物浓度由3 010.13 mg/L降为194.16 mg/L、氟化物浓度由1.57 mg/L降为0.31 mg/L、硼浓度由4.04 mg/L降为1.62 mg/L。确定该区地热尾水处理的最佳组合工艺为采用超滤运行压力为0.1 MPa,纳滤膜为陶氏NF90,操作压力为0.60 MPa,进水量为0.8 m3/h。室内实验溶解性总固体去除率90.21%～92.49%,氯化物去除率91.63%～93.02%,氟化物去除率96.81%,硼去除率55.20%～55.69%。中试试验溶解性总固体去除率为92.62%;氯化物浓度200 mg/L,氯化物去除率为92.57%;硼浓度1.77 mg/L,硼去除率为55.7%,以上实验结果均达到相关规范标准。试验证明本工艺处理松嫩盆地北部林甸地热田供暖尾水是可行的,解决了供暖尾水处理中资源浪费和尾水回收利用的技术性问题,为地热资源可持续利用提供了新的途径。     

太阳辐射管理地球工程对海洋酸化影响的模拟研究

研究地球工程对海洋酸化的影响对于评估地球工程对全球气候和环境的影响有重要意义。文中使用中等复杂程度的地球系统模式,模拟了典型CO₂高排放情景RCP8.5下,实施太阳辐射管理地球工程对海洋表面的pH和文石（碳酸钙的一种亚稳形态）饱和度的影响,并定量分析了各环境因子对海洋酸化影响的机理。模拟结果表明,在RCP8.5情景下,到2100年,相对于工业革命前水平,全球海洋表面平均pH下降了0.43,文石饱和度下降了1.77。相对于RCP8.5情景,2100年地球工程情景下全球海洋表面平均pH增加了0.003,而文石饱和度降低了0.16。地球工程通过改变溶解无机碳、碱度、温度等环境因子影响海洋酸化。相对于RCP8.5情景,实施地球工程引起的溶解无机碳浓度的增加使pH和文石饱和度均减小,碱度的增加使pH和文石饱和度均增大,温度的降低使pH增大而使文石饱和度减小。总体而言,太阳辐射管理地球工程可以降低全球温度,但无法减缓海洋酸化。     

Latitudinal and Scan-dependent Biases of Microwave Humidity Sounder Measurements and Their Dependences on Cloud Ice Water Path

The relationship between differences in microwave humidity sounder(MHS)–channel biases which represent measured brightness temperatures and model-simulated brightness temperatures, and cloud ice water path(IWP) as well as the influence of the cloud liquid water path(LWP) on the relationship is examined. Seven years(2011–17) of NOAA-18 MHS-derived measured brightness temperatures and IWP/LWP data generated by the NOAA Comprehensive Large Array-data Stewardship System Microwave Surface and Precipitation Products System are used. The Community Radiative Transfer Model, version2.2.4, is used to simulate model-simulated brightness temperatures using European Center for Medium-Range Weather Forecasts reanalysis data as background fields. Scan-angle deviations of the MHS window channel biases range from-1.7 K to1.0 K. The relationships between channels 2, 4, and 5 biases and scan angle are symmetrical about the nadir. The latitudedependent deviations of MHS window channel biases are positive and range from 0–7 K. For MHS non-window channels,the latitudinal deviations between measured brightness temperatures and model-simulated brightness temperatures are larger when the detection height is higher. No systematic warm or cold deviations are found in the global spatial distribution of difference between measured brightness temperatures and model-simulated brightness temperatures over oceans after removing scan-angle and latitudinal deviations. The corrected biases of five different MHS channels decrease differently with respect to the increase in IWP. This decrease is stronger when LWP values are higher.     

UNIT HYDROGRAPH DERIVED FROM A SPATIALLY DISTRIBUTED VELOCITY FIELD

A unit hydrograph model is proposed in which the watershed is decomposed into subareas which are individual cells or zones of neighbouring cells. The unit hydrograph is found for each subarea and the response at the outlet to excess rainfall on each subarea is summed to produce the watershed runoff hydrograph. The cell to cell flow path to the watershed outlet is determined from a digital elevation model. A constant flow velocity is assigned to each cell and the time lag between subarea input and response at the watershed outlet is found by integrating the flow time along the path from the subarea to the outlet. The response function for a subarea is modelled as a lagged linear reservoir in which the flow time is equal to the sum of a time of translation and an average residence time in the reservoir. It is shown that the assumption of a spatially varying, but time-invariant, velocity field underlying this model produces a linear system model for all subareas whose outputs can be summed in the manner indicated. An example application is presented for the 8.70 km² Severn watershed at Plynlimon in Wales using a 50 m digital elevation model in which the cell velocity is calculated by modifying an average watershed velocity according to the terrain slope and the drainage area of each cell. The resulting model reasonably reproduces the observed unit hydrograph.     

SNOW WETNESS ESTIMATES OF VEGETATED TERRAIN FROM SATELLITE PASSIVE MICROWAVE DATA

The Special Sensor Microwave/Imager (SSM/I) radiometer is a useful tool for monitoring snow wetness on a large scale because water content has a significant effect on the microwave emissions at the snowpack surface. To date, SSM/I snow wetness algorithms, based on statistical regression analysis, have been developed only for specific regions. Inadequate ground-based snow wetness measurements and the non-linearity between SSM/I brightness temperatures (T_Bs) and snow wetness over varied vegetation covered terrain has impeded the development of a general model. In this study, we used a previously developed linear relationship between snowpack surface wetness (% by volume) and concurrent air temperature (°C) to estimate the snow wetness at ground weather stations. The snow condition (snow free, dry, wet or refrozen snow) of each SSM/I pixel (a 37 × 29 km area at 37.0 GHz) was determined from ground-measured weather data and the T_B signature. SSM/I T_Bs of wet snow were then linked with the snow wetness estimates as an input/output relationship. A single-hidden-layer back-propagation (backprop) artificial neural network (ANN) was designed to learn the relationships. After training, the snow wetness values estimated by the ANN were compared with those derived by regression models. Results show that the ANN performed better than the existing regression models in estimating snow wetness from SSM/I data over terrain with different amounts of vegetation cover.