Mineral carbonation as a design project for green chemical engineering education

Accelerated mineral carbonation is a promising CO2 sequestration technology that is strongly linked to concepts of sustainability and Green Chemistry, and its process requirements apply principles of reaction kinetics, transport phenomena, and materials characterization. The present work aimed to develop educational tools for including accelerated mineral carbonation in chemical engineering curricula. To this end, an experimental investigation laboratory procedure and a design project outline have been conceived. As a way to further engage students in this learning experience, the process conditions for the laboratory work are varied between groups of students, and the experimental data obtained are pooled to be used by every group for the subsequent design exercise. This is meant to give students motivation to generate accurate data that they knew would be useful for the entire class and, at the same time, provide students with the opportunity to use data generated by colleagues, much in the same way the design work is done in the industry. In the design project, students use the experimental data obtained by themselves and classmates on the accelerated mineral carbonation of wollastonite, to determine if this is a feasible process for industry to sequester carbon dioxide, in view of mitigating climate change. Also, they use the experimental data, acquired using a range of process conditions, to study the effect of the process variables (CO2 pressure and mixing rate) on the carbonation kinetics and mass transfer rate. The focus of our previously published article was on the experimental investigation, while the focus of this conference paper is on the design project.


Introduction
One of the biggest concerns with the accelerated mineral carbonation technology is that if it is implemented as an industrial process, it will not deliver net CO2 sequestration. The reason behind this is that all process equipment in the industry requires energy to function, and, in most cases, that energy is supplied from CO2-intensive processes. Even so-called "green energy" has a CO2 footprint. Hydroelectric fares the best, at 4 g, CO2-eq/kWhe, while wind and solar emit (over the life-cycle) 12 and 22 g, CO2-eq/kWhe, respectively (CO2-eq stands for CO2-equivalent, and kWhe is the rate of electrical energy generation) [1]. At the other end of the spectrum, the median CO2 intensity of coal power generation, the worst performer, is a whopping 1001 g, CO2-eq/kWhe. Thus, if too much energy is used for accelerating mineral carbonation, the process may end up emitting more CO2 than sequestering it. Due to the energetic challenges posed, it is vital to conduct an energetic analysis of any proposed accelerated mineral carbonation process. For example, Santos et al. [2] found that, for an ultrasoundenhanced mineral carbonation process (at lab-scale), for every 2.3 g of CO2 sequestered, 79.2 g would be emitted (based on the energy-mix of Belgium). They proposed some strategies to reduce the CO2 emissions further at the industrial-scale, such as securing a less CO2-intensive energy source, increasing the solids loading in the reactor (i.e., more solids per volume of liquid), and improving the design of the reactor to maximize the utilization of sonication energy. Still, a 100-factor reduction in CO2-intensity would be necessary to achieve net CO2 sequestration, so it is not easy and perhaps not feasible.
More recently, for a more conventional carbonation process, utilizing steelmaking slag as the carbon sink, Costa et al. [3] estimated an energy requirement of 272−1750 kWh/tonne CO2 sequestered. Based on the aforementioned energy-intensity of wind power generation, this would represent 38 kg, CO2 emitted per 1000 kg, CO2 sequestered. Hence, this would be a feasible process for net CO2 sequestration. It should be noted, however, that steelmaking slags require less intense carbonation conditions compared to wollastonite (as the material is more reactive). Unfortunately, there is far less steelmaking slag being produced than CO2 being emitted by steelmaking, so this material alone cannot substantially reduce emissions from this CO2-intensive industry. Thus, natural materials, such as wollastonite, more abundantly available (though more expensive due to mining and transportation costs), are required to curtail industrial emissions.
So the question is, can accelerated carbonation of wollastonite become a feasible industrial process for net CO2 sequestration? This can be addressed in an educational setting through a design project, herein proposed. This project is suitable for implementation in upper-year undergraduate (Bachelor or Advanced Diploma) engineering and engineering technology programs, and also for graduate courses at the Master's level.

Design project procedure
The following paragraphs highlight the main steps in the design procedure.
First, assemble a process flowsheet for sequestering CO2 using wollastonite. The process starts with mined, coarse grade (80% passing 8 mm) wollastonite, and CO2 that has been captured from a flue gas source. Capturing means concentrating the CO2 from an industrial source (typically 10-30% CO2 by volume) into a pure (>99 vol%) CO2 stream). You must take the energy consumption of the capturing step into account (see table A1, in the Appendix), but you can ignore the energy consumption of wollastonite mining and transport. The process must use the following equipment (listed in arbitrary order): a. pressurized, jacket heated, continuously stirred tank reactor. b. CO2 multi-stage compressor. c. slurry pump(s). d. heat exchanger(s). e. solid/liquid separator (unspecified type). f. size reduction grinder/mill (unspecified type).
Second, determine what process conditions you will use. Choose the combination of process conditions, from the experiments conducted by all students, that yielded the highest carbonation conversion, and conversely the highest CO2 uptake.
The third step is to determine the scale of the process. That is, how much CO2 is to be sequestered. For this, ideally, you should choose a rate of CO2 sequestration that matches the rate of CO2 emissions from a particular industrial facility (e.g., coal power plant, steelmaking mill, cement factory, pulp and paper plant, to name a few). Your flowsheet will have a single reactor, which should have a feasible size, so choose an emissions source that will fit the scale of the process you are able to design, or propose to capture only a fraction of the emissions with the single reactor if the scale is too large. It is your task to research emissions values and make an appropriate design choice. Assume that all CO2 IOP Publishing doi:10.1088/1757-899X/1196/1/012009 3 that is compressed will be sequestered (i.e., there are no gaseous emissions). Based on the amount of CO2 to be sequestered (tonnes/day), and the maximal CO2 uptake (tonnes,CO2/tonne, wollastonite) you are able to achieve (from the previous step), you can determine the amount of wollastonite (tonnes/day) that you will need to process.
Fourth is step is that once you know the amount of wollastonite that you will need to process, you can determine slurry volume and consequently the size of the reactor. Remember that the reactor is a batch process, so there is only so much wollastonite slurry that can be processed per batch, and only so many batches that can be processed per day (based on filling, heating and emptying times). Use your lab experiment experience, and your batch reactor theory and design knowledge, to make a suitable determination of the reactor size. You will not need to size any of the other equipment for this design exercise; it will be assumed that each equipment's energy consumption depends only on throughput and not on physical size.
In the fifth step, calculate the energy consumption of each process/equipment using the equations given in Table A. Table A presents the equations needed, along with definitions and units of each equation parameter, and suggestive values for some parameters. Other parameter values will come from the process conditions used in the lab experiment (that gave the best carbonation conversion), such as the mixing rate (G, in s -1 ). Other parameters will have to be researched or assumed (e.g., the dynamic viscosity (μ) of the slurry); use justifiable assumptions. You can neglect the slurry pumping power. Note that the units for each energy term differ (kWh/tonne, Wh, J, etc.); these will have to be converted to a common energy unit (kWh/tonne CO2 sequestered) before being summed to obtain the total energy consumption value.
In the sixth step, for the slurry heating power, take into account how much exothermic energy is produced in the reactor during the reaction, how much energy is lost to the environment by natural convection, and how much waste heat may be re-used to pre-heat the feed using a heat-exchanger. Some additional assumptions will be required (e.g., heat-exchange efficiency). Based on this analysis, you only need to take into account in the overall energy balance what extra heating energy is required that will consume external power.
For the seventh and final step, once you have the total energy consumption value, per tonne CO2 sequestered, determine if the process achieves net CO2 sequestration. That is, convert the energy consumption value into a carbon emission value, using an assumed CO2-intensity value of power generation (find this value for Ontario), and compare the rate of emission to the rate of sequestration. Assume that all energy requirement for the process comes from electrical power obtained from the provincial grid.

Reaction rate law
In the energetic analysis, you will use experimental data to decide what the maximal CO2 uptake of wollastonite is. However, during experimentation, only a limited number of experiments were performed. So it may be that the maximal CO2 uptake occurs with a CO2 pressure different than the values tested (maybe even higher or lower than the range covered). It is thus helpful for design purposes to obtain a rate law that describes how CO2 pressure affects the carbonation rate.
In the Experimental Investigation [4], a rate law proposed by Ptáček et al.
[5] was introduced, which accounted for the effect of temperature on the rate of carbonation. That law, which is based on the well-known Arrhenius equation, required experimental determination of two empirical parameters: the pre-exponential factor (A), and the activation energy (EA). Values for these two parameters, suggested by Ptáček et al., were cited: 1.8 ± 0.9•103 s −1 for A in the case of wollastonite dissolution in acetic acid, and 47 ± 1 kJ/mol for EA. It should be noted, however, that these values were obtained from experimental studies on the dissolution of wollastonite in acetic acid, rather than its dissolution and immediate precipitation, as it occurs when wollastonite is exposed to carbonic acid (i.e., CO2 at elevated pressure in contact with an aqueous slurry of wollastonite). It should also be noted that the value of EA obtained experimentally is "apparent", meaning that it is a measure value based on a specific set of process conditions, rather than the true activation energy based on fundamental To take into account the effect of CO2 pressure, in addition to temperature, a possibly suitable rate law is an extended version of the Arrhenius equation, as follows: where rmincarb is the mineral carbonation rate (mol/(m 2 •s)), A is the pre-exponential empirical factor (mol/(m 2 •s)), EA is the apparent activation energy of carbonation (kJ/mol), R is the universal gas constant (kJ/(mol•K)), T is the temperature (K), PCO2 is the partial pressure of CO2 (bar), and y is the order of reaction.
Also recall that the rate of carbonation (Rcarb (mol/s)) is proportional to the available mineral surface area (Amin,(t) (m 2 )) (Eq. 2), which itself is a function of time (Eq. 3). ξ(t) is the fractional extent of carbonation conversion of the mineral at the reaction time and mwo,init is the initial mass of wollastonite being carbonated (g), and SSA is the initial specific surface area (m 2 /g).
Amin,(t) = SSA • (1 -ξ(t)) • mwo,init Hence, the first step in this analysis will be to convert the experimental carbonation conversions (ξ(30min)) and rates of carbonation (Rcarb) into reaction rates (rmincarb). The value of Rcarb will be calculated from the total CO2 uptake value, and it will be assumed that the rate of carbonation is linear in the first 30 minutes (this is in agreement with the work of Huijgen et al. [6]).
Once values of rmincarb are obtained for every experiment (with varying CO2 pressures and mixing rates), the rate law will be fitted to the data to account for the effect of pressure. For this, it is best to divide the data into sets of constant mixing rate, and for each set, fit the data based on variation of pressure alone. Fitting of the data should be done by plotting experimental and calculated values of rmincarb versus PCO2, and adjusting parameters to minimize the difference between the lines. Having three unknowns (A, EA and y), and no data on the effect of temperature, you will need to use some discretion in adjusting these parameters to fit the available data. For example, you may wish to use the values of Ptáček et al. [5] for A and EA at first, solve for y, and then adjust A or EA to better fit the experimental data trend. Repeat this for each mixing rate set to find out if the mixing rate has a large effect on the rate law, and if so on which rate parameter.

Mass transfer analysis
Mass transfer of ions in the aqueous mineral carbonation system occurs in two mediums: the solid phase and the liquid phase. In the solid phase, ion transport is governed by the diffusivity of the ions through the mineral matrix, with porosity and ion-solid interactions playing a role in aiding or restricting ion transport compared to the simple diffusion mechanism. In the liquid phase, mixing plays an important role in inducing convection in the bulk phase, in aiding the dissolution of CO2 from the gaseous phase (which is over the liquid surface), and in reducing the thickness of the stagnant liquid film at the surface of solid particles. This increases the driving force for the transport of ions from and to the solid surface.
In this mass transfer analysis, you will focus on the effect of mixing rate on the rate of carbonation using the experimental data set you are given. In the experimental study, the mixing rate was varied along with CO2 partial pressure. By dividing the data set into sub-sets, you can isolate the effect of mixing rate for a given CO2 partial pressure. One question to address is if mixing can compensate for a lower CO2 partial pressure, as the energy consumption of mixing is expected to be lower than the energy consumption of compressing CO2 (is this what the energetic analysis indicated?). Another question to address is what the rate limiting step of the reaction is: mineral dissolution, ion diffusion IOP Publishing doi:10.1088/1757-899X/1196/1/012009 5 through the solid phase, or ion diffusion in the liquid phase (either from the solid phase or from the gaseous phase)?
To investigate the effect of the mixing rate, you will look at the Sherwood Number (Sh), which indicates if diffusion or convection dominates the mass transfer in the liquid phase. A high value of Sh implies that there is sufficient mixing to overcome diffusion limitations. But if the carbonation rate does not improve markedly with higher rate of mixing, it will indicate that the rate limiting step lies elsewhere. In that case, an assessment of the rate of diffusion through the solid phase, and comparison of that rate with the reaction rate, would further indicate if mineral dissolution or solid-phase mass transfer is rate-limiting.
The correlation between mass transfer and agitation is made by the Sherwood Number (Sh), which is a dimensionless number that represents the ratio of the convective rate of mass transfer to the rate of diffusive mass transport (Eq. 4) [7]. The value of Sh has been found to be a function of two additional dimensionless numbers common in the field of transport phenomena (Eq. 5): the Reynolds Number (Re), defined in Eq. 6 for an impeller-stirred tank; and the Schmidt Number (Sc), defined in Eq. 7.
where L is a characteristic length (m), which in the case of particles is the particle diameter [7], D is mass diffusivity (m 2 •s −1 ), K is the convective mass transfer film coefficient (m•s −1 ), ρL is the density of the liquid (kg/m 3 ), N is the rotational speed of the impeller (s -1 ), DI is the diameter of the impeller (m), μL is the dynamic viscosity of the liquid (Pa·s), and DL is the diffusion coefficient of the chosen species in the liquid phase (m 2 /s).
The actual value of Sh must be determined using empirical correlations. Many experimental studies of mass transfer from a particle to a fluid exist, some of which concern the dissolution of solid particles. The choice of a suitable equation should be based on the one that best fits experimental observations for the system in question. In the absence of prior experience, an equation that has been found to fit a variety of data reasonable well is the Frössling Equation (Eq. 8), which is valid for a wide range of Sc and Re up to 1000 [8].

Report requirements
1. The report should contain the following sections: cover page , table of contents, table of figures,  table of

Conclusions
The ultimate objective of the proposed design project is to better train chemical engineering students given their future careers. Graduates with experience in mineral carbonation investigation and design would potentially be better trained to develop engineering solutions that take into account sustainability criteria. Also, having gone through a memorable undergraduate exercise in mineral carbonation investigation and design would potentially reinforce learned concepts of chemical engineering fundamentals, and make it more likely that graduate would recall those fundamental concepts in their future careers.