Seasonal controls on sediment transport and deposition in Lake Ohau,South Island,New Zealand: Implications for a high‐resolution Holocene palaeoclimate reconstruction

Laminated sediments in Lake Ohau, Mackenzie Basin, New Zealand, offer a potential high‐resolution climate record for the past 17 kyr. Such records are particularly important due to the relative paucity of detailed palaeoclimate data from the Southern Hemisphere mid‐latitudes. This paper presents outcomes of a study of the sedimentation processes of this temperate lake setting. Hydrometeorological, limnological and sedimentological data were collected over a 14 month period between 2011 and 2013. These data indicate that seasonality in the hydrometeorological system in combination with internal lake dynamics drives a distinct seasonal pattern of sediment dispersal and deposition on a basin‐wide scale. Sedimentary layers that accumulate proximal to the lake inflow at the northern end of the lake form in response to discrete inflow events throughout the year and display an event stratigraphy. In contrast, seasonal change in the lake system controls accumulation of light (winter) and dark (summer) laminations at the distal end of the lake, resulting in the preservation of varves. This study documents the key processes influencing sediment deposition throughout Lake Ohau and provides fundamental data for generating a high‐resolution palaeoclimate record from this temperate lake.     

基于扫描电镜-氮气吸脱附和压汞法的页岩孔隙结构研究

研究页岩孔隙结构特征,对于探讨页岩气赋存机理有重要意义。本文采用扫描电镜(SEM)、氮气吸脱附法与压汞法对鄂尔多斯盆地页岩样品的孔隙结构进行了全面表征,发现所研究区域页岩孔隙类型包括溶蚀孔隙、粒间孔隙和微裂缝;孔径从几个纳米到几百个微米,BET比表面积在7~25 m~2/g之间,孔体积在0.01~0.03 cm~3/g范围。研究结果表明鄂尔多斯盆地页岩具有良好的孔隙结构,孔隙类型丰富,孔径分布范围广泛,其中纳米级孔隙占主导,纳米级孔的存在有利于页岩气的存储,微裂隙的存在则有利于页岩气的运移。说明该区域页岩气的储藏具有良好的基础环境,页岩含气量可能较丰富。     

利用原子荧光光谱-电感耦合等离子体质谱法研究济南市大气干湿沉降重金属含量及年沉降通量特征

大气降尘是地表土壤重金属元素的重要来源,研究大气降尘中重金属元素的地球化学特征并进行源解析对制定污染防控政策具有重要的指导作用。本文采用原子荧光光谱法、电感耦合等离子体质谱法、X射线荧光光谱法分析济南市大气干湿沉降中8种重金属(砷镉铬铜汞镍铅锌)含量特征;采用相关分析及主成分分析方法对大气干湿沉降重金属进行源解析。结果表明,大气干湿沉降物中镉铬铜汞镍铅锌平均含量分别为2.07 mg/kg、135.9 mg/kg、65.7 mg/kg、218.6μg/kg、110.7 mg/kg、380 mg/kg,显著高于土壤背景值,且富集程度高,明显受人为活动污染。镉铜汞铅主要来源于燃煤,砷铬来源于道路尘,镍来源于土壤,锌来源于交通尘;燃煤和道路尘对大气降尘的贡献率为50.13%,两者是济南市大气降尘污染的主要来源。大气干湿沉降对城区表层土壤中镉汞铬铅锌及砷的含量水平影响显著,其中锌年沉降通量最高(均值148 mg·m-2·a-1),汞年沉降通量最低(均值0.085 mg·m-2·a-1),且镉汞含量增长速率较高;大气干湿沉降对砷铬在土壤中的累积影响显著。     

新疆伊犁盆地黄土古气候记录与Heinrich事件对比分析

伊犁盆地作为中国黄土高原与欧洲黄土区的过渡区域,其第四纪古气候研究对于揭示全球气候驱动及耦合机制具有重要的意义.通过对伊犁盆地塔勒德晚更新世黄土-古土壤剖面粒度、低频磁化率及地球化学元素分析,探讨了西风区黄土-古土壤序列中古气候指标变化特征及记录的全球气候突变事件.结果表明:古土壤层中粒径10μm颗粒物含量明显高于黄土层,与之相反的是古土壤层中的低频磁化率、Zr/Rb值和元素Ti含量均小于黄土层,且元素Ti含量与Zr/Rb间具有较高的相关性.黄土-古土壤剖面中古气候代用指标清晰的记录了6次Heinrich(H)事件及Younger Drays(YD)事件,但YD事件、H1、H2、H5和H6事件变幅较H3和H4事件显著,古气候指标与格陵兰冰芯δ18O、季风区李家塬粒度和洛川、西峰及环县Zr/Rb值均具有较好的一致性,所记录的气候事件较李家塬、洛川、西峰更为显著.结合已有研究说明,Heinrich和D-O旋回等气候事件是由西风区向季风区传递的,MIS3阶段温度的升高和常年受西风的影响是造成塔勒德气候环境变化特征的主要控制因素.     

水稻冠层氮素含量光谱反演的随机森林算法及区域应用

利用地面实测数据构建高精度的水稻冠层氮素含量光谱反演点模型并将其进行尺度转换,实现了水稻冠层氮素含量准实时、大区域监测。以氮素光谱敏感指数作为输入变量,冠层氮素含量数据为输出变量,利用随机森林算法构建水稻冠层氮素含量高光谱反演模型,并用苏州市水稻农田验证区数据,检验模型的普适性和有效性;利用准同步的Hyperion数据,采用对输入、输出变量进行线性变换的简单尺度转换方法实现了点模型的区域应用。结果表明:基于随机森林算法的水稻冠层氮素含量高光谱反演模型可解释、所需样本少、不会过拟合、精度高(模型在实验区的预测精度为R2=0.82,验证区检验精度为R2=0.73)且具有普适性;点模型基于高光谱遥感卫星影像和尺度转换进行区域应用,精度较高(R2=0.81)。     

早期成岩作用过程中硫酸盐还原反应研究进展

文章概述近年来早期成岩作用中硫酸盐还原反应研究的某些新资料和新成果 ,综合分析了各种沉积环境下的早期成岩作用中的硫酸盐还原反应。重点论述贫氧缺氧条件下的反应机制。并讨论了判别沉积环境的Fe -C -S的关系及黄铁矿的形成和碳酸盐的溶解、沉淀与氧化还原带的对应关系。简要讨论了早期成岩作用中硫酸盐还原反应的研究意义。     

Hydrogeochemical characteristics of spring water in the Harz Mountains,Germany

Spring water samples of the Harz Mountains were taken in several seasons of 2010, 2011, and 2012. The samples have been analysed for main components (Na⁺, K⁺, Ca²⁺, Mg²⁺, SO₄²⁻, Cl⁻, HCO₃⁻ and NO₃⁻), trace elements (Fe, Cu, Pb, Zn, Y and REE), DOC, δ¹⁸O and δ²H of water. Meteoric water is indicated as the main source of the springs sampled. High precipitation rates lead to a dilution of the measured elemental concentrations. Furthermore, regional differences of rock and water interactions were found. REE concentrations and patterns of the spring waters vary between the distinct geological units and reflect the geochemical characteristics of the surrounding rocks. The actual data compared to measured data from the seventies and nineties of the last century indicate a decrease of the sulphate concentrations in the spring waters which is typical of many European mountain catchments.     

Nitrogen dioxide DOAS measurements from ground and space: comparison of zenith scattered sunlight ground-based measurements and OMI data in Central Mexico

The use of satellite data in combination with ground-based measurements can provide valuable information about atmospheric chemistry and air quality. In this study, ground-based Differential Optical Absorption Spectroscopy (DOAS) measurements of nitrogen dioxide (NO₂) conducted in central Mexico are compared with the space-borne Ozone Monitoring Instrument (OMI) dataset of 2006-2011. Ground-based measurements exhibited large day-to-day variations and were on average three times higher than the space-borne derived average over the observation site. This difference is attributed to strong horizontal inhomogeneity of the lower layer of the measured NO₂ columns, sampled over a large footprint from the satellite instrument. Also, a reduced sensitivity of the satellite observation near the surface, where the largest concentrations are expected, could be responsible for this large discrepancy. From the analyzed OMI dataset, distribution maps of NO₂ above central Mexico were reconstructed, allowing to identify three main areas with increased NO₂ column densities: The dominating metropolitan area of Mexico City, the heavily industrialized region of Tula to the north and the Cuernavaca valley to the south. In this analysis, seasonal variability of NO₂ columns over central Mexico was detected, finding higher NO₂ columns during the dry and cold season, followed by the dry and warm period, and finally the lowest NO₂ columns were found during the rainy season. Pollution transport of this gas from Tula into Mexico City, as well as towards the Cuernavaca valley, is evident from this dataset.     

Monitoring nitrogen concentration of oilseed rape from hyperspectral data using radial basis function

Remote sensing technology is the important tool of digital earth, it can facilitate nutrient management in sustainable cropping systems. In the study, two types of radial basis function (RBF) neural network approaches, the standard radial basis function (SRBF) neural networks and the modified type of RBF, generalized regression neural networks (GRNN), were investigated in estimating the nitrogen concentrations of oilseed rape canopy using vegetation indices (VIs) and hyperspectral reflectance. Comparison analyses were performed to the spectral variables and the approaches. The Root Mean Square Error (RMSE) and determination coefficients (R²) were used to assess their predictability of nitrogen concentrations. For all spectral variables (VIs and hyperspectral reflectance), the GRNN method produced more accurate estimates of nitrogen concentrations than did the SRBF method at all ranges of nitrogen concentrations, and the better agreements between the measured and the predicted nitrogen concentration were obtained with the GRNN method. This indicated that the GRNN method is prior to the SRBF method in estimation of nitrogen concentrations. Among the VIs, the Modified Chlorophyll Absorption in Reflectance Index (MCARI), MCARI₁₅₁₀, and Transformed Chlorophyll Absorption in Reflectance Index are better than the others in estimating oilseed rape canopy nitrogen concentrations. Compared to the results from VIs, the hyperspectral reflectance data also gave an acceptable estimation. The study showed that nitrogen concentrations of oilseed rape canopy could be monitored using remotely sensed data and the RBF method, especially the GRNN method, is a useful explorative tool for oilseed rape nitrogen concentration monitoring when applied on hyperspectral data.     

Modelling nitrogen dynamics for a mesoscale catchment using a minimum information requirement (MIR) concept / Modélisation des dynamiques de l'azote pour un bassin versant de taille moyenne,utilisant le concept de besoin minimum d'information

Abstract

Based on the water balance model LARSIM (Large Area Simulation Model), a model for the simulation of nitrogen transport was developed in a mesoscale catchment in southwest Germany. To meet the needs and constraints in river basin management, the nitrogen model was developed following the concept of minimum information requirement (MIR). The modelling concept uses only few calibration parameters and only easily accessible input data. Water balance, runoff generation and nitrogen transport were simulated on a 1-km² grid of sub-areas in which different land-use classes and soil characteristics were accounted. Temporal variability of the storage of mobile nitrogen were described using a monthly based mass balance. Nitrogen mobilization and transport was simulated using monthly values of different runoff components and data for soil properties, topography, hydrogeology and river network. The simulation was calibrated and validated using streamflow from two gauging stations and observed nitrogen concentrations at the catchment outlet, showing reasonable results for both streamflow and nitrogen dynamics. The results of the model application are discussed in the context of uncertainty problems and their implications for water management.