Spatial variability of the poroelastic response of the heterogeneous medium

In this work, a stochastic methodology is applied to analyze the variability of the poroelastic response of the heterogeneous medium at the field scale. To solve the problem analytically, we restrict our attention to the one-dimensional models, where fluid flow as well as deformation occurs in one direction only under a constant applied stress. Assuming statistic homogeneity, the closed-form solutions that describe the variability of fluid pressure head, and a solid's strain and displacement are developed using a spectral approach based on Fourier–Stieltjes representations for the perturbed quantities. The influence of the correlation length of the log hydraulic conductivity on these results is investigated. It is found that the variances of the solid's strain and displacement increase with the correlation length of the log hydraulic conductivity, while the correlation length of the log hydraulic conductivity plays the role in reducing the variability of the specific discharge.     

Analysis of the impact of injection mode in transport through strongly heterogeneous aquifers

Large-scale advective transport through highly heterogeneous 3D formations is investigated using highly resolved numerical simulations and simple analytic models. Investigations are focused on impacts of two types of contaminant injection on transport through isotropic formations where flow conditions are uniform in the average. Transport is quantified by analyzing breakthrough curves for control planes at various distances from the injection zone. In flux-proportional injection mode local mass in injection zone is proportional to local groundwater flux; this setup models many practical cases such as contaminant injection through wells. In resident concentration mode local concentration in injection zone is constant. Results show that impacts of injection mode on breakthrough curves and their moments are strong and they persist for hundreds of correlation scales. The resident concentration mode leads to a fatter tails of the breakthrough curves, while the peaks are generally underpredicted. For a synthetic porous medium with logconductivity variance of 8, dispersivity computed using resident concentration mode at control plane 100 integral scales away from the injection zone was about 10 times larger than corresponding one for flux-proportional mode. Hence, injection mode impacts on transport through highly heterogeneous formations are strong and they persist for large distances from the injection zone.     

Interpretation and nonuniqueness of CTRW transition distributions: Insights from an alternative solute transport formulation

The continuous time random walk (CTRW) has both an elegant mathematical theory and a successful record at modeling solute transport in the subsurface. However, there are some interpretation ambiguities relating to the relationship between the discrete CTRW transition distributions and the underlying continuous movement of solute that have not been addressed in existing literature. These include the exact definition of “transition”, and the extent to which transition probability distributions are unique/quantifiable from data. Here, we present some theoretical results which address these uncertainties in systems with an advective bias. Simultaneously, we present an alternative, reduced parameter CTRW formulation for general advective transport in heterogeneous porous media, which models early- and late-time transport by use of random transition times between sparse, imaginary planes normal to flow. We show that even in the context of this reduced-parameter formulation there is nonuniqueness in the definitions of both transition lengths and waiting time distributions, and that neither may be uniquely determined from experimental data. For practical use of this formulation, we suggest Pareto transition time distributions, leading to a two-degree-of-freedom modeling approach. We then demonstrate the power of this approach in fitting two sets of existing experimental data. While the primary focus is the presentation of new results, the discussion is designed to be pedagogical and to provide a good entry point into practical modeling of solute transport with the CTRW.     

基于模式分析一次沙尘暴过程中沙尘表面非均相化学过程对中国地区污染物浓度的影响

利用戈达德对地观测系统（GEOS）提供的再分析气象场GEOS-5驱动的GEOS-Chem模式,模拟中国地区2009年4月22~29日沙尘暴期间沙尘气溶胶表面非均相化学过程对我国污染物的影响。模拟结果表明,沙尘暴期间,全国平均沙尘硝酸盐和沙尘硫酸盐浓度分别为0.2 μg m-3和0.4 μg m-3,占总硝酸盐（非沙尘硝酸盐与沙尘硝酸盐之和）和总硫酸盐（非沙尘硫酸盐与沙尘硫酸盐之和）的24%和10%。我国西部地区沙尘硝酸盐占比（ > 80%）要大于其他地区,而西部地区的沙尘硫酸盐占比则要小于下游地区。考虑非均相化学反应后,沙尘暴期间,全国平均的二氧化硫（SO₂）、硝酸（HNO₃）、臭氧（O₃）、非沙尘硫酸盐、总硫酸盐、非沙尘硝酸盐、总硝酸盐、NH₃、总铵盐浓度变化量分别为-7%、-15%、-2%、-8%、3%、-2%、14%、21%、-5%。     

Condensation particle counting below 2 nm seed particle diameter and the transition from heterogeneous to homogeneous nucleation

Particle detection by condensation particle counters (CPCs) is ultimately limited by the onset of homogeneous nucleation. At vapour supersaturations around the homogeneous nucleation limit the diameter of critical clusters is typically about 2 nm. It is widely assumed that only particles larger than critical clusters can be activated by vapour condensation and the general detection limit of CPCs is therefore currently accepted to be around 2 nm particle diameter. Using an expansion type CPC with n-propanol as working fluid we investigated the transition from heterogeneous to homogeneous nucleation, clearly showing that particles are activated much before the onset of homogeneous nucleation, even at particle diameters as small as 1.4 nm. For particle diameters below 2 nm we have usually found condensation particle counting to be influenced by the simultaneous presence of ions as generated in a bipolar diffusion charger. In this paper we illustrate how the presence of ions influences particle number concentration measurement and how ions can be removed in order to obtain accurate seed particle number concentrations for particle diameters down to 1 nm.     

Conditional Probability Density Functions of Concentrations for Mixing-Controlled Reactive Transport in Heterogeneous Aquifers

This paper presents an approach conducive to an evaluation of the probability density function (pdf) of spatio-temporal distributions of concentrations of reactive solutes (and associated reaction rates) evolving in a randomly heterogeneous aquifer. Most existing approaches to solute transport in heterogeneous media focus on providing expressions for space–time moments of concentrations. In general, only low order moments (unconditional or conditional mean and covariance) are computed. In some cases, this allows for obtaining a confidence interval associated with predictions of local concentrations. Common applications, such as risk assessment and vulnerability practices, require the assessment of extreme (low or high) concentration values. We start from the well-known approach of deconstructing the reactive transport problem into the analysis of a conservative transport process followed by speciation to (a) provide a partial differential equation (PDE) for the (conditional) pdf of conservative aqueous species, and (b) derive expressions for the pdf of reactive species and the associated reaction rate. When transport at the local scale is described by an Advection Dispersion Equation (ADE), the equation satisfied by the pdf of conservative species is non-local in space and time. It is similar to an ADE and includes an additional source term. The latter involves the contribution of dilution effects that counteract dispersive fluxes. In general, the PDE we provide must be solved numerically, in a Monte Carlo framework. In some cases, an approximation can be obtained through suitable localization of the governing equation. We illustrate the methodology to depict key features of transport in randomly stratified media in the absence of transverse dispersion effects. In this case, all the pdfs can be explicitly obtained, and their evolution with space and time is discussed.     

Key Methods and Experiment Verification for the Validation of Quantitative Remote Sensing Products

The validation is an important guarantee of quality, reliability and applicability of Remote Sensing Products (RSPs), and is also the foundation to improve the RSPs accuracy, extend the application domain and strength the application ability. This paper introduced the progresses and lessons learned from a project titled by ‘key technology of remote sensing products validation and its experimental evaluation’ supported by Ministry of Science and Technology of China. The progresses included: ①Formulating a series of national standards composed of general methods for the validation of terrestrial quantative RSPs, field-site selection and instrumentation for land surface RSPs, and other 24 individual standards of remote sensing variables; ②Building integral technique process system of RSPs validation; ③Developing some key methods from optimized spatial sampling, upscaling to validation strategy; ④Obtaining the multi-scale satellite-airborne-ground synchronized observation and evaluating systematically the validation standard and techniques; ⑤Setting up national validation network for RSPs, exploring multi-mode allied observation experiment and forming the prototype and operation mechanism for the validation network.     

Analysis of solute transport with a hyperbolic scale-dependent dispersion model

An empirical hyperbolic scale-dependent dispersion model, which predicts a linear growth of dispersivity close to the origin and the attainment of an asymptotic dispersivity at large distances, is presented for deterministic modelling of field-scale solute transport and the analysis of solute transport experiments. A simple relationship is derived between local dispersivity, which is used in numerical simulations of solute transport, and effective dispersivity, which is estimated from the analysis of tracer breakthrough curves. The scale-dependent dispersion model is used to interpret a field tracer experiment by nonlinear least-squares inversion of a numerical solution for unsaturated transport. Simultaneous inversion of concentration-time data from several sampling locations indicates a linear growth of the dispersion process over the scale of the experiment. These findings are consistent with the results of an earlier analysis based on the use of a constant dispersion coefficient model at each of the sampling depths.