This lesson introduces Reactive Transport Models (RTMs), primarily focusing on a brief history of RTM development, governing equations, and key concepts. It includes a lightboard video about the governing RT equations, a video that introduces the code that we will use in this class, CrunchFlow, and the reading materials here. The idea here is to give you an overview of RTM. Many concepts introduced here will be detailed in later lessons so it is OK if you do not fully grasp them in this lesson.
Please note that this is not a course that teaches how to numerically solve for reactive transport equations, which deserve a separate course by itself. Instead, this is a course that teaches fundamental reactive transport concepts and how to use an existing software CrunchFlow to solve and answer specific questions. So this is a model application course, not a numerical method course.
By the end of this lesson, you should:
There are example files and hw files in each lesson (almost). If you would like extra exercise files, click here [1].
(Optional) Reading |
Note: these are your references. You can skip through quickly in this lesson to get some overview idea. You will use these again and again later. |
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To Do |
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If you have any questions, please post them to our Questions? discussion forum (not e-mail), located in Canvas. I will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you, too, are able to help out a classmate.
Reactive transport models have been applied to understand biogeochemical systems for more than three decades (Beaulieu et al., 2011; Brown and Rolston, 1980; Chapman, 1982; Chapman et al., 1982; Lichtner, 1985; Regnier et al., 2013; Steefel et al., 2005; Steefel and Lasaga, 1994). Multi-component RTMs originated in the 1980s based on the theoretical foundation of the continuum model (Lichtner, 1985; Lichtner, 1988). RTM development advanced substantially in the 1990s with the emergence of several extensively-used RTM codes, including Hydrogeochem (Yeh and Tripathi, 1991; Yeh and Tripathi, 1989), CrunchFlow (Steefel and Lasaga, 1994), Flotran (Lichtner et al., 1996), Geochemist’s Workbench (Bethke, 1996), Phreeqc (Parkhurst and Appelo, 1999), Min3p (Mayer et al., 2002), STOMP (White and Oostrom, 2000), TOUGHREACT (Xu et al., 2000), among others (Ortoleva et al., 1987, Bolton, 1996). Several early diagenetic models were developed at similar times, including STEADYSED (Van Cappellen and Wang, 1996), CANDI (Boudreau, 1996), and OMEXDIA (Soetaert et al., 1996). These codes can be easily found through google their names.
RTMs are distinct from geochemical models that primarily calculate geochemical equilibrium, speciation, and thermodynamic state of a system (Wolery et al., 1990). RTMs also differ from reaction path models (Helgeson, 1968; Helgeson et al., 1969) that represent closed or batch systems without diffusive or advective transport. The major advance of modern RTMs was to couple flow and transport within a full geochemical thermodynamic and kinetic framework (Steefel et al., 2015).
RTMs have been used across an extensive array of environments and applications (as reviewed in MacQuarrie and Mayer, 2005; Steefel et al., 2005). One primary focus has been in the low-temperature (ca < 100˚C) surface and near-surface environment where “rock meets life”, a region often referred to as the Critical Zone (CZ). Within the critical zone, water, atmosphere, rock, soil, and life interact creating the potential for complex chemical, physical, and biological interactions and responses to external forcing. As illustrated in Figure 0.1, RTMs can simulate a wide range of processes in this environment, including fluid flow (single or multiphase), solute transport (advective, dispersive, and diffusive transport), geochemical reactions (e.g., mineral dissolution and precipitation, ion exchange, surface complexation), and biogeochemical processes (e.g., microbe-mediated redox reactions, biomass growth and decay).
RTMs with these capabilities have been applied to understand chemical weathering and soil formation in response to various biological, climatic and physical drivers. RTMs have also been essential to address a wide range of questions at the nexus of energy and the environment, including, for example, environmental bioremediation (Bao et al., 2014), natural attenuation (Mayer et al., 2001), geological carbon sequestration (Apps et al., 2010; Brunet et al., 2013; Navarre-Sitchler et al., 2013), and nuclear waste disposal (Saunders and Toran, 1995; Soler and Mader, 2005). Model frameworks have advanced to incorporate heterogeneous characteristics of natural systems to begin to understand the role of spatial heterogeneities in controlling flow and the interaction between water and reacting components (Scheibe et al., 2006; Yabusaki et al., 2011; Liu et al., 2013). With the expansion of isotopes as tracers of mineral-fluid and biologically mediated reactions, recent advances include development of RTMs that allow an explicit treatment of isotopic partitioning due to both kinetic and equilibrium process.
The RTM approach has also been used to investigate subsurface processes at spatial scales ranging from single pores (Kang et al., 2006; Li et al., 2008; Molins et al., 2012) and single cells (Scheibe et al., 2009; Fang et al., 2011), to pore networks and columns (1 -10s centimeters) (Knutson et al., 2005; Li et al., 2006; Yoon et al., 2012; Druhan et al., 2014), and to field scales (1-10’s of meter) (Li et al., 2011), with a few studies at the watershed or catchment scale (100s of meters) (Atchley et al., 2014). Recent weathering studies have linked regional scale reactive transport models (WITCH) to global climate models to understand the role of climate change in controlling weathering (Godderis et al., 2006; Roelandt et al., 2010). Recent model development also includes full coupling between subsurface biogeochemical processes and surface hydrology, land-surface interactions, meteorological and climatic forcings (Bao et al., 2017; Li et al., 2017a). Such coupling has been argued to be important in understanding the complex interactions between processes of interests in different disciplines (Li et al., 2017b).
Most reaction transport codes solve equations of mass, momentum, and energy conservation (Steefel et al., 2005). For mass conservation, reactive transport models usually partition aqueous species into primary and secondary species (Lichtner, 1985). The primary species are the building blocks of chemical systems of interest, upon which concentrations of secondary species are written through laws of mass action for reactions at thermodynamic equilibrium. The partition between primary and secondary species allows the reduction of computational cost by only solving for mass conservation equations for primary species and then calculating secondary species through thermodynamics. Detailed discussion on primary and secondary species will be in lesson 1 on Aqueous Complexation.
Please watch the following video: Reactive Transport Reactions (7:25)
The following is a representative mass conservation equation for a primary species I in the aqueous phase:
Here Ci is the total concentration of species i (mol/m3 pore volume), t is the time (s), n is the number of primary species, D is the combined dispersion–diffusion tensor (m2/s), u (m/s) is the Darcy flow velocity vector and can be decomposed into ux and uz in the directions parallel and transverse to the main flow direction. Nr is the total number of kinetic aqueous reactions that involve species i,
Equation (1) implies that the mass change rate of species i depends on physical and chemical processes: the diffusion/dispersion processes that are accounted for by the first term of the right hand side of the equation, the advection process that is taken into account by the second term of the right hand side, and reactions that are represented by the last term of the equation. The last term is the summation of multiple reaction rates, the form of which depend on the number and type of kinetic reactions that species i is involved in. The reaction terms include the rates of kinetically controlled reactions including microbe-mediated bioreduction reactions, mineral dissolution and precipitation reactions, and redox reactions. The reactions also include fast reactions that are considered at thermodynamics equilibrium, including aqueous complexation, ion exchange, and surface complexation. These fast reactions that are at equilibriums however do not show up in the above governing equation (1). Instead they exhibit themselves in the non-linear coupling of primary and secondary species through the expression of equilibrium constants (laws of mass action), as will be detailed later.
The dispersion-diffusion tensor D is defined as the sum of the mechanical dispersion coefficient and the effective diffusion coefficient in porous media D*(m2/s). At any particular location (grid block) with flow velocities in longitudinal (L) and transverse (T) directions, their corresponding diffusion / dispersion coefficients DL (m2/s) and DT (m2/s) are calculated as follows:
Here αL and αT are the longitudinal and transverse dispersivity (m). The dispersion coefficients vary spatially due to the non-uniform distribution of the permeability values.
As will be discussed in lesson 1, in a system with N total number of species and m fast reactions, the total number of primary species is n = N – m. With specific initial and boundary conditions, reactive transport codes solve a suite of n equation (1) with explicit coupling of the physical processes (diffusive/dispersive + advective transport) together with m algebraic equations defined by the laws of mass action of fast reactions. The output is the spatial and temporal distribution of all N species. This type of process-based modeling allows the integration of different processes as a whole while at the same time differentiation of individual process contribution in determining overall system behavior.
The focus of this course is on how to use an existing reactive transport code, not on how to numerically solve reactive transport equations, which deserves a separate course by itself. Readers who are interested in numerical methods of RTM are referred to book chapters and literature for details of discretization of the equations and numerical solution.
The rest of the course is structured as follows. Unit 1 includes lessons that teach principles and set up of geochemical reactions in well-mixed systems (zero-dimension in space, well-mixed systems). In this unit, the equations solved are ordinary differential equations (ODEs) with time as the independent variable however without space dimensions. Lesson 1 focuses on the concepts of primary and secondary species, reaction thermodynamics, and aqueous complexation reactions. Lesson 2 teaches mineral dissolution and precipitation reactions and Transition State Theory (TST) rate law. Lesson 3 is on surface complexation reactions. Lesson 4 teaches ion exchange reactions. Lesson 5 teaches microbe-mediated reactions.
Unit 2 teaches principles and set up of solute transport processes. This is where we introduce the space dimension. Here we solve Advection-Dispersion equation (ADE) without reactions in a one-dimensional system (lesson 6). Lesson 7 teaches principles and set up of heterogeneous, two dimensional domains.
Unit 3 combines biogeochemical reactions in Unit 1 and solute transport processes in Unit 2. Lesson 9 is an example of 1D transport with multiple mineral dissolution and precipitation reactions. If you run the simulation sufficiently long and allow the properties change over time, it becomes a chemical weathering simulation. Lesson 9' intends to have you combine solute transport with microbe-mediated reactions based on lessions 5 and 6. Lesson 10 introduces a 2D system with both physical and geochemical heterogeneities.
CrunchFlow was developed by Carl I. Steefel [2] in the 1990s (Steefel and Lasaga, 1994). It has been continuously evolving with new capabilities and features. Please refer to the CrunchFlow webpage for detailed introduction of code capabilities [3]. Among various existing reactive transport code, we choose to teach CrunchFlow owing to its features that allows each incorporation, computational efficiency with the use of fast solvers from the petsc (Portable, Extensible Toolkit for Scientific Computation) library, and its flexibility in simulating spatailly heterogeneous systems.
CrunchFlow executables: There are several different versions of CrunchFlow executables in Canvas. They are for different operation systems: windows – 32 bit, windows – 64 bit, and Mac. Please download the version that is compatible to the operating system on your PC. For windows executables, you need a dynamic library (.dll file) to run the exe, which is also in the corresponding Canvas folder. The Mac executables do not need a dynamic running library.
CrunchFlow Orientation:
In input file:
Please watch the video (32:46 minutes) Lesson 0 Crunch Flow Orientation that introduces CrunchFlow and its database and input file structure.
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In this orientation we have an overview of the history of RTM development and the applications of RTMs in the past decades. We also discussed general reactive transport equations and the physical meaning of different terms. At the end we introduce CrunchFlow, the code we will learn to use in this class.
You have reached the end of Lesson 0! Double-check the to-do list on the Lesson 0 Overview page [15] to make sure you have completed all of the activities listed there. Please download CrunchFlow compatible with your PC, and run the example files following the instructions in the video. Please report any problems if it does not work so we can help you set up.
Links
[1] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/ExtraExercisesFiles/CrunchFlow.zip
[2] http://esd.lbl.gov/about/staff/carlsteefel/, https://scholar.google.com/citations?user=Yv-KZG0AAAAJ&hl=en
[3] http://www.csteefel.com/CrunchFlowIntroduction.html
[4] https://creativecommons.org/licenses/by-nc-sa/4.0/
[5] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/CrunchFlowManual.pdf
[6] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/0LessonCrunchFlowOrientation.pdf
[7] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/CrunchTope-32bit.exe
[8] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/libiomp5md.dll
[9] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/CrunchTope-64bit.exe
[10] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/libiomp5md_0.dll
[11] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/CrunchTope
[12] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/CrunchTope-Mac
[13] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/transport1D.in
[14] https://www.e-education.psu.edu/ce574/sites/www.e-education.psu.edu.ce574/files/FileUploads/datacom.dbs
[15] https://www.e-education.psu.edu/ce574/698