Large time behavior of differential equations with drifted periodic coefficients modeling Carbon storage in soil

This paper is concerned with the linear ODE in the form $y'(t)=\lambda\rho(t)y(t)+b(t)$, $\lambda <0$ which represents a simplified storage model of the carbon in the soil. In the first part, we show that, for a periodic function $\rho(t)$, a linear drift in the coefficient $b(t)$ involves a linear drift for the solution of this ODE. In the second part, we extend the previous results to a classical heat non-homogeneous equation. The connection with an analytic semi-group associated to the ODE equation is considered in the third part. Numerical examples are given.Comment: 18 page

Hydrobiogeophysics: Linking geo-electrical properties and biogeochemical processes in shallow subsurface environments

Microbially mediated reactions drive (bio)geochemical cycling of nutrients and contaminants in shallow subsurface environments. Environmental forcings exert a strong control on the timing of reactions and the spatial distribution of processes. Spatial and temporal variations in electron acceptor and donor availability may modulate nutrient/contaminant turnover. Characterizing the preferential spatial-zonation of biologically driven reactions, and quantifying turnover rates is hindered by our inability to access the subsurface at the spatial and temporal resolution required to capture reaction kinetics. Typical subsurface sampling methods generate discrete spatial datasets as a function of the prohibitive cost and operational challenges of borehole installation and core sampling, coupled with sparse temporal datasets due to intermittent sampling campaigns. In order to improve our ability to access biogeochemical information within the subsurface, without the need for destructive and intrusive sampling, non-invasive geophysical techniques (a comparatively inexpensive alternative) have been proposed as a means to characterize subsurface reactive compartments and locate zones of enhanced microbial activity and the timing of their development. The challenge lies in linking electrical responses to specific changes in biogeochemical processes. In this thesis, I assess the potential and suitability of spectral induced polarization (SIP) and self-potential (SP) / electrodic potential (EP) derived geo-electrical signals to detect, map, monitor and quantify microbially mediated reactions in partially- and fully-saturated heterogeneous porous media (i.e., soil). I build on existing literature delineating the sensitivity of SIP, SP and EP to biogeochemical processes and both qualitatively and quantitatively link geo-electrical signal dynamics to specific microbial processes at the experimental scale. I address the monitoring of complex, coupled processes in a well-characterized near-natural system, and combine reactive transport models (RTMs) with single-process reactive experiments (reduced complexity), to isolate diagnostic signatures of specific reactions and processes of interest. In Chapter 2, I begin by monitoring biogeochemically modulated geo-electrical signals (SIP and EP), in the variably (and dynamically) saturated reactive zone within the capillary fringe of an artificial soil system. SIP and EP responses show a clear dependence on the depth-distribution of subsurface microbes. Dynamic SIP imaginary conductivity (σ'') responses are only detected in the water table fluctuation zone and, in contrast to real conductivity (σ') data, do not exhibit a direct soil moisture driven dependence. Using multiple lines of evidence, I attribute the observed σ'' dynamics to microbially driven reactions. Chapter 2 highlights that continuous SIP and EP signals, in conjunction with periodic measurements of geochemical indicators, can help determine the location and temporal variability of biogeochemical activity and be used to monitor targeted reaction zones and pathways in complex soil environments. Building on the findings from Chapter 2, that biomass distribution and activation strongly modulate SIP responses, in Chapter 3 and 4, I focus on isolating the geo-electrical contribution of microbes themselves. In Chapter 3, I couple geochemical data, a biomass-explicit diffusion reaction model and SIP spectra from a saturated sand-packed (with alternating layers of ferrihydrite-coated and pure quartz sand) column experiment, inoculated with Shewanella oneidensis, and supplemented with lactate and nitrate. The coupled RTM and geo-electrical data analysis show that imaginary conductivity peaks parallel simulated microbial growth and decay dynamics. I compute effective polarization diameters, from Cole-Cole modeling derived relaxation times, in the range 1 – 3 µm; two orders of magnitude smaller than the smallest quartz grains in the columns, suggesting that polarization of the bacterial cells directly controls the observed chargeability and relaxation dynamics. In Chapter 4, I address the lack of experimental validation of biomass concentrations in Chapter 3. I present a measurement-derived relationship between S. oneidensis abundance and SIP imaginary conductivity, from a microbial growth experiment in fully saturated sand-filled column reactors. Cole-Cole derived relaxation times highlight the changing surface charging properties of cells in response to stress. The addition of concurrent estimates of cell size allow for the first measurement-derived estimation of an apparent Stern layer diffusion coefficient for cells, which validates existing modelled values and helps quantify electrochemical polarization during SIP-based monitoring of microbial dynamics. The relaxation time results from Chapter 4 suggest that bacterial cell surface charge is modified in response to nitrite toxicity-induced stress. In Chapter 5, I present a biomass-explicit reactive transport model, which integrates nitrite-toxicity, as a key modulator of the energy metabolism of S. oneidensis, to predict the rates of nitrate and nitrite reduction. I validate the model with results from two separate experiments (at different experimental scales): (1) a well-mixed batch suspension and (2) the flow-through reactor experiment from Chapter 4. The incorporation of toxicity-induced uncoupling of catabolism and anabolism in the reactive term predicts the observed delay in biomass growth, facilitated by endogenous energy storage when nitrite is present, and consumption of these reserves after its depletion. The model is further validated by the close agreement between the trends in imaginary conductivity and simulated biomass growth and decay dynamics. Finally, in Chapter 6, I apply the RTM-SIP integrative framework from Chapters 3 and 5 to develop quantitative relationships between SIP signals and engineered nanoparticle concentrations. Therein, SIP responses measured during injection of a polymer-coated iron-oxide nanoparticle suspension in columns packed with natural aquifer sand are coupled to output from an advective-dispersive transport model. The results highlight the excellent agreement between simulated nanoparticle concentrations within the columns and SIP signals, suggesting that polarization increases proportional to increasing nanoparticle concentration. The results from Chapter 6, introduce the possibility of quantitative SIP monitoring of coated metal-oxide nanoparticle spatial and temporal distributions. Overall, my results show the applicability of SIP and EP to map and monitor the spatial zonation of biogeochemical hotspots and to detect their temporal activation. By coupling RTMs with geo-electrical datasets, I highlight the direct control that polarization of microbial cells exerts on SIP signals in biotic systems. Furthermore the measurement-derived SIP-biomass quantitative relationship provides a first attempt to directly measure in situ biomass density, using geo-electrical signals as a proxy. I show that geo-electrical signal dynamics (Cole-Cole relaxation time) can be used to inform processes within RTMs. Finally, the implementation of the combined modeling and electrical monitoring approach, to the case of engineered nanoparticles, confirms SIP’s suitability to monitor colloid transport in the environment and highlights considerations for method optimization

Linking Montane Soil Moisture Measurements to Evapotranspiration Using Inverse Numerical Modeling

The mountainous areas in the Intermountain West (IMW) of the North America are considered as the major water reservoir for the Western US. Summer evapotranspiration (ET) and soil moisture are key factors affecting the annual water yield in the montane region of the IMW. This research estimated ET of four common vegetation types (aspen, conifer, grass, and sage) and areal soil moisture in an advanced instrumentation site located at the T.W. Daniel Experimental Forest (TWDEF). Among instrumented forest research sites worldwide, TWDEF is one of a few with triplicate measures of meteorological parameters, radiation, and soil moisture within four common vegetation types in the IMW. This unique dataset enables study and understanding of the ecological and hydrological responses to climate change in Utah and the IMW region. In a second phase of this study, summer water uses from the four common vegetation types were simulated using a numerical simulation model, Hydrus-1D. The simulation was informed by soil moisture measurements at three depths (0.1 m, 0.25 m, and 0.5 m) and by ET measured from an eddy covariance tower. The results confirmed the value of numerical simulations as a viable alternate method to estimated ET where no direct ET measurements are available. It also provided comparison of water use by these vegetation species including both high and low water years. In the third phase of this study, a comparison was made between the intermediate-scale areal soil moisture measured by a Cosmic-ray neutron probe (CRNP) and the in situ TDT soil moisture network at the TWDEF site. Improved correlations were obtained, especially after shallow rainfall events, by including numerically simulated soil moisture above 0.1 m where no measurements were available. The original CRNP calibration exhibited a dry bias during spring/early summer, leading to the need for a site-specific enhanced calibration, which improved the accuracy of the CRNP soil moisture estimate at the TWDEF site

The deep space network, volume 15

The DSN progress is reported in flight project support, TDA research and technology, network engineering, hardware and software implementation, and operations. Topics discussed include: DSN functions and facilities, planetary flight projects, tracking and ground-based navigation, communications, data processing, network control system, and deep space stations

A Technique for Predicting the Aquatic Ecosystem Response to Weather Modification

In the past, considerable effort has been spent on the development of techniques for increasing precipitation from a given cloud formation. However, little attention has been given to identifying and evaluating the impacts of cloud seeing activities on the aquatic ecosystems within the affected areas. The objective of this study was to apply the simulation technique to predict the impacts of cloud seeing on the aquatic ecosystem within the area subject to weather modification. A small mountain watershed near Logan, Utah, was selected for the study. Measurements were made of the significant parameter levels under current conditions. A hydrologic and water temperature model was calibrated to the watershed to predict the change in water temperature and stream velocities from arbitrary increases in the snowpack. The predicted water velocities and temperatures were used to link the hydrologic system to the aquatic ecosystem which consisted of primary production, invertebrate, and fish communities. The study was conducted over a very short time base, and thus cannot be regarded as being absolutely conclusive, but the results do indicate trends which might be expected if various decreases of water temperature and increases in stream velocity were to occur

Generation of (synthetic) influent data for performing wastewater treatment modelling studies

The success of many modelling studies strongly depends on the availability of sufficiently long influent time series - the main disturbance of a typical wastewater treatment plant (WWTP) - representing the inherent natural variability at the plant inlet as accurately as possible. This is an important point since most modelling projects suffer from a lack of realistic data representing the influent wastewater dynamics. The objective of this paper is to show the advantages of creating synthetic data when performing modelling studies for WWTPs. This study reviews the different principles that influent generators can be based on, in order to create realistic influent time series. In addition, the paper summarizes the variables that those models can describe: influent flow rate, temperature and traditional/emerging pollution compounds, weather conditions (dry/wet) as well as their temporal resolution (from minutes to years). The importance of calibration/validation is addressed and the authors critically analyse the pros and cons of manual versus automatic and frequentistic vs Bayesian methods. The presentation will focus on potential engineering applications of influent generators, illustrating the different model concepts with case studies. The authors have significant experience using these types of tools and have worked on interesting case studies that they will share with the audience. Discussion with experts at the WWTmod seminar shall facilitate identifying critical knowledge gaps in current WWTP influent disturbance models. Finally, the outcome of these discussions will be used to define specific tasks that should be tackled in the near future to achieve more general acceptance and use of WWTP influent generators

Mass Transfer in Multiphase Systems and its Applications

This book covers a number of developing topics in mass transfer processes in multiphase systems for a variety of applications. The book effectively blends theoretical, numerical, modeling and experimental aspects of mass transfer in multiphase systems that are usually encountered in many research areas such as chemical, reactor, environmental and petroleum engineering. From biological and chemical reactors to paper and wood industry and all the way to thin film, the 31 chapters of this book serve as an important reference for any researcher or engineer working in the field of mass transfer and related topics

The National Aeronautics and Space Administration interdisciplinary studies in space technology at the University of Kansas

A broad range of research projects contained in a cooperative space technology program at the University of Kansas are reported as they relate to the following three areas of interdisciplinary interest: (1) remote sensing of earth resources; (2) stability and control of light and general aviation aircraft; and (3) the vibrational response characteristics of aeronautical and space vehicles. Details of specific research efforts are given under their appropriate departments, among which are aerospace engineering, chemical and petroleum engineering, environmental health, water resources, the remote sensing laboratory, and geoscience applications studies