Ismael Matito-Martos

Claudia Sepúlveda

Cintia Gómez

Gabriel Acién

Julio Perez-Carbajo

José A Delgado

V I Águeda

Maria Conchi

Ovin Concepcion

José Ania

Sofía Parra

Calero

: ⟨10 Doi

Claudia Sepulveda
email: claudia.sepulveda@uantof.cl

Ania Conchi

J B Parra

S Calero

J A Anta
email: anta@upo.es

Potential of CO2 capture from flue gases by physicochemical and biological methods: A comparative study

Keywords: CO 2 capture, zeolites, microalgae, light efficiency

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

The relationship between Global Warming and increasing emissions of Green House Gases (GHG) is not more under discussion, most of the countries signing the Paris Protocol to mitigate the anthropogenic emissions of these gases. 1 Thus, countries are enforced to implement real mitigation strategies considering reduction of GHG emission both by improvement of the technology for energy production and the development of technologies for GHG capture. Among the different GHG, carbon dioxide is one of the most relevant for the larger magnitude of its emission, mainly related with energy production for fossil fuels 2 . A reduction in power consumption or improvements to combustion processes can help reducing CO 2 emissions. Alternatively, carbon capture and storage (CCS) shows great potential in diminishing the amount of CO 2 released into the atmosphere from industrial and civil combustion processes 3,4 . CCS refers to strategies for capturing CO 2 from flue gases followed by long-term storage for hundreds of years; these are capable of contributing up to 55 % to the mitigation effort 3 . Different technologies have been proposed for CO 2 capture, 5 the most conventional being based on ammines-related absorption processes, 6 other using membranes 7 or including cryogenic processes 8 to capture the CO 2 from the flue gases. A major problem related with these technologies is the large energy consumption, the difficulty to recover the CO 2 gas, and its tolerance to the corrosive conditions imposed by the flue gases composition 9 . Additionally, the utilization of porous materials for CO 2 adsorption in Pressure Switch Adsorption (PSA) processes has been also proposed. 10 This technology requires less energy and also facilitates the recovery of the CO 2 gas by using a readily available driving force such as the pressure difference between the high feed pressure for adsorption and a lower pressure for desorption. However, PSA methods still rely on the availability of materials with improved properties in terms of CO 2 adsorption capacity and selectivity. Materials that have been thoroughly studied are mainly inorganic zeolites, 11 metal organic frameworks 12 , as well as the functionalization of these with room temperature ionic liquids 13 among others. It must be born in mind that whatever the CO 2 capture process is, energy consumption must remain low and, besides, the final product, in the form of a concentrated CO 2 stream, must be valorised.

As an alternative to chemical and physicochemical techniques, the utilization of microalgae for CO 2 capture process has also been proposed. This biological process has been reported to require less energy, thus it is potentially more sustainable from the environmental point of view. However, biological methods are more sensible to pollutants contained into the flue gases and their typical rate of CO 2 capture is lower than that of chemical processes. 14,15 In spite of that, they have the critical advantage of providing a final product (microalgae biomass) that would be more valuable than the CO 2 stream of the chemical and physicochemical methods, thus positively contributing to the economic sustainability of the entire process. There is a lot of studies about the application of microalgae for CO 2 capture, most of them related with the production of biofuels, all of them concluding that the reliability of the process is highly dependent on the strains tested, production scale/technology and final application of the biomass. Moreover, the large surface and the overall cost of the technology are actually bottlenecks for the commercial development of microalgae-based CO 2 capture processes. [16][17][18][19] In the last years, the large scale production of microalgae is fast increasing mainly by two reasons: (i) the enlargement of the market as microalgae biomass is now included in more food/feed products, and (ii) the improvement of the technology allowing to increase the biomass productivity, thus reducing the biomass production costs. Some important advances includes the development of more robust strains (improved strains non genetically modified), improvement of energy utilization efficiency and mass transfer capacity on the reactors, and development of new downstream strategies and products. [20][21][22][23][24] These advances make the possibility of using microalgae for CO 2 capture process much more realistic today than twenty years ago, especially if combined with the treatment of other wastes as wastewater or manure. 19,25 Thus, the growth potential of microalgae-based methods can be up to 100 times faster than terrestrial plants, thus achieving productivities of 100 tn/ha•year.

To achieve these figures, large amounts of nutrients are required: for each tonne of biomass produced, it takes up to 2 tnCO 2 , 100 kgN and 10 kgP. This can actually be provided by flue gases and wastewater. 20 Additionally, large surfaces and adequate environmental conditions (light, temperature, etc..) are required, factors such as pH, temperature and light intensity have a great influence on the growth dynamics of microalgae as do the nutrients 26 .

The aim of this work is to re-think the CO 2 capture process taking into account the actual technology available in order to determine the real suitability of novel processes at different scales. We will focus our study on zeolite-based CO 2 adsorption (physicochemical process) and microalgae-based CO 2 capture (biological process). In both cases, a common composition of flue gas, with varying CO 2 concentrations, typical of industrial combustion activities, have been considered. On the one hand, a combination of molecular simulation, numerical modelling of the continuous PSA process and equilibrium adsorption experiments has been used to assess the potentiality of CO 2 capture of the physicochemical method. On the other hand, a 100 m 2 pilot scale raceway reactor has been used to evaluate the capability of the biological process under real outdoor conditions in terms of biomass production and CO 2 capture efficiency. In both cases a previous screening has been done to select the optimum zeolite (physicochemical process) and the optimum microalgae strain (biological process). Figures from the reactor experiment allows to evaluate the energy consumption and cost of the biological process, and to compare it with their physicochemical counterpart. Considering final applications of the biomass the suitability of both processes at commercial scale is finally discussed.

MATERIALS AND METHODS

Theoretical determination of adsorption isotherms in zeolites

Adsorption isotherms were computed using Monte Carlo simulations in the Grand Canonical ensemble (GCMC). In this ensemble, the average value of the temperature, the volume, and the chemical potential remain fixed. The chemical potential directly relates to fugacity, and then fugacity to pressure by the fugacity coefficient through the Peng-Robinson equation of state. [START_REF] Frenkel | Understanding Molecular Simulations: From Algorithms to Applications[END_REF] The MC trial moves employed were translation, rotation, and reinsertion of gas molecules, swap from the reservoir, and identity change for mixtures. [START_REF] Frenkel | Understanding Molecular Simulations: From Algorithms to Applications[END_REF] Results were obtained after running 10 3 equilibration and 5•10 3 production cycles, respectively. In the case of water, up to 2•10 6 production cycles were used in order to equilibrate some particular pressure points. The number of Monte Carlo steps per cycle equals the total number of molecules in the system with a minimum of 20. Described simulations are performed using the simulation code RASPA. [START_REF] Dubbeldam | [END_REF]29 Atomic interactions were taken into account by electrostatic interactions, considered by using Coulombic potential and Ewald summations; and van der Waals interactions, described by 12-6 Lennard-Jones potential. [START_REF] Frenkel | Understanding Molecular Simulations: From Algorithms to Applications[END_REF] In both cases, the cutoff distance is set to 12 Å, where the interactions are truncated and shifted with no tail corrections applied. These simulation conditions are commonly used to study adsorption in confined systems. 30,31 Adsorbate molecules were all considered rigid, as they are already reported for CO 2 , 32 N 2 , 33 O 2 , 33 and H 2 O. 34 Details and parameters of the interaction model used for these molecules can be found in the Supporting Information (Section A, Table S1)

Six widely employed zeolites with different geometry and topology were selected for this work (i.e. BEA, FAU, FER, ITQ-29, MFI, and MOR). Most of them are commercially available and used for different gas separations. We use a pure-silica version of these zeolites, considering them as rigid frameworks as it is well-known that the effect of zeolite flexibility is usually small in adsorption studies. 35 A representation of the grid surface energy of the selected materials is presented in Fig. S1. A description of the morphology and crystalline structure of these zeolites as considered in the modeling is also included in the Supporting Information (Section B, Figure S2, Table S2).

The insertion of molecules using Monte Carlo can take place in cavities or channels experimentally accessible only for some small adsorbates, such as H 2 or H 2 O. To avoid this artificial insertion of molecules and reproduce experimental behavior, these cavities need to be carefully blocked. 36,37 As in previous works, we use Monte Carlo and Molecular Dynamics (MD) simulations to identify these inaccessible cavities. 38,39 First we identify energetic preferential adsorption sites for the molecules using MC, and then MD informs about the diffusion of the molecules. These sites from which molecules are unable to escape after 0.15 ns were properly blocked. In RASPA, the blockage is implemented using a list of geometric descriptions of the inaccessible volumes that are automatically considered as an overlap in MC simulations. Using this methodology, sodalites in FAU and ITQ-29 and y-axis channels in FER were blocked for all the molecules under study (except for H 2 O) due to narrow access windows do not allow diffusion of these molecules.

Experimental determination of adsorption isotherms in MFI zeolite

Experimental equilibrium gas adsorption isotherms for pure gases (CO 2 and air) and for a mixture of 10 % CO 2 in air were recorded on pure silica MFI zeolite at room temperature using a volumetric analyser (Micromeritics) in the pressure range between 10 -2 and 120 kPa. The zeolite was outgassed under dynamic vacuum at 623 K (1K/min) overnight before the gas adsorption measurements. All the gases were supplied by by Air Liquide with an ultra high purity (i.e., 99.995%). Pure silica MFI zeolite was supplied by Institute of Chemical Technology, CSIC, Spain.

Pressure Swing Adsorption (PSA) simulations

Typical flue gas at ambient conditions mixture (0.75 N 2 , 0.10 CO 2 , 0.11 O 2 , and 0.032 H 2 O at 298 K and 1 bar) was considered in the PSA simulations. A simple Skartrom PSA cycle in isothermal conditions was first considered to compare the separation performance of the different 6 zeolites simulated in Section 2.1, because the model resolution is quite faster than with more complex cycles. Although industrial PSA processes usually operate adiabatically, the isothermal conditions can be achieved if the bed diameter is reduced and heat exchange rate between the bed and the surroundings is increased. A detailed cycle description is presented in Fig. S3 in the Supporting Information. Operating conditions and model parameters are given in Table S3. The high pressure (P H ) of the cycle is defined to 1 bar to avoid the energy consumption on compressing the feed gas. A low pressure (P L ) of 0.1 bar is used as it is a typical limit considered for practical application of PSA technology. 40,41 It is also assumed that the adsorbent crystals are agglomerated in pellets, and that mass transfer between gas and adsorbent is controlled by macropore diffusion, neglecting intracrystalline resistance. 42 The multicomponent adsorption isotherms for the PSA simulations were obtained by applying the Ideal Adsorption Solution Theory (IAST) 43 , previously obtained by GCMC simulations. Isotherms were fitted with the Langmuir equation. 44 Details of the simulations and the fit are summarized in the Supporting Information (Section C)

In order to improve the yield of the CO 2 separation predicted in the previous PSA Skarstrom cycle, a dual-PSA cyle with three equalization steps in adiabatic conditions, with MFI zeolite as adsorbent in the bed was also implemented. 45 The dual-PSA cycle includes two coupled PSA cycles where one cycle increases the CO 2 concentration to an intermediate value (rectifying PSA) and the other increases further the CO 2 concentration up to the desired specification (stripping PSA). The same PSA cycle has been used for each one of the coupled cycles. The individual PSA cycle is presented in Fig. S4a in the Supporting information. Light product and tail gas are obtained at 1 bar. The way of coupling the individual PSA cycles for the dual configuration is presented in Fig. S4b.

Other parameters used in the simulations (except gas velocities) are given in Table S3. To model the effect of temperature on the adsorption isotherms, the pure adsorption isotherms of all the components in MFI have been obtained by GCMC simulation, and they have been fitted with the temperature dependent Langmuir model (q = K H0 exp (-H/RT) p / (1+b 0 exp (-H/RT) p). A comparison between the fitted isotherms and the molecular simulation data is presented in Fig. S6, and the obtained Langmuir parameters are presented in Table S6.

Microorganisms and culture media

Different microorganisms, microalgae and cyanobacteria, were preselected according to previous experience and the literature; more than 40 reference works being reviewed in depth for that. Only robust strains suitable for large-scale production under non-optimally controlled conditions were selected (Table S7 in the Supporting Information). Some of the microorganisms were already available at the University of Almeria whilst others were obtained from official culture collections, mainly from the Culture Collection of Algae and Protozoa (Oban, Scotland). Inoculum from all the strains were kept under controlled conditions in 1 L flasks, at 20 °C, under constant illumination at 200 μE•m -2 •s -1 provided by fluorescent lamps, with constant aeration at 0.1 v/v/min with no CO 2 supply in a standard Arnon culture medium. The standard culture medium was prepared using freshwater and Mann & Myers medium prepared using fertilizers (0.14 g•L -1 K(PO 4 ) 2 , 0.18 g•L -1 Mg(SO 4 ) 2 , 0.9 g•L -1 NaNO 3 , 0.02 mL•L -1 Welgro, and 0.02 g•L -1 Kalentol), it being autoclaved at 121 °C for 15 minutes only for laboratory trials. The inoculum cultures were monitored by microscopic observation using a Leica CME microscope 40X/0.65 to verify non-contamination.

Laboratory photobioreactors

Experiments were performed in bubble-column photobioreactors (~ 300 mL) aerated at 0.2 v/v/min with pH controlled at 8.0 by on-demand injection of real flue gas (from a diesel boiler). The temperature inside the reactors was kept at 25ºC by controlling the temperature of the chamber in which the reactors are located. A total of 15 bubble-column reactors were used and each experiment was tested in triplicate. The reactors are illuminated artificially using fluorescent lamps that are automatically turned on or off to simulate the circadian solar cycle. Irradiance on the reactors surface (I o ) varied throughout the day from zero to 1200 µE•m -2 •s -1 at noon -using these values, a mean irradiance for the light period (I light ) of 780 µE•m -2 •s -1 was obtained. On a 24 h basis, the mean irradiance on the reactor surface (I day ) was 390 µE•m -2 •s -1 .

Experiments were performed in continuous mode. For this, we used inoculum from previous cultures developed in flasks but without pH control and under continuous illumination at 200 µE•m -2 •s -1 . The volume of inoculum supplied to the reactors at the beginning of the experiment was 10% of the total culture volume in the bubble column.

Once the reactor was inoculated, it was operated in batch mode for 5 days, after that it was operated in semicontinuous mode at 0.3 day -1 dilution rate (medium inlet and harvesting are performed during illuminated period), till steady state was achieved (at least two times the hydraulic retention time). During the experiments the cultures were daily monitored measuring the biomass concentration and the fluorescence of chlorophylls. Water evaporation was compensated for each day with distilled water to avoid changes in conductivity or of any nutrient in the culture broth. At the end of the experiment, when a steady state was achieved, the entire culture was harvested and the biomass was stored for biochemical composition analysis.

Outdoor raceway

The raceway reactor is located at the "Las Palmerillas" Research Centre, 36° 48′N-2° 43′W, part of the Cajamar Foundation (Almería, Spain). The reactor consists of two 50 m long channels (0.46 m high × 1 m wide), both connected by 180° bends at each end, with a 0.59 m 3 sump (0.65 m long × 0.90 m wide × 1 m deep) located 1 m along one of the channels. 46 A paddlewheel system was used to recirculate the culture through the reactor at a regular velocity of 0.2 m•s -1 , although it can be increased up to 0.8 m•s -1 by manipulating the frequency inverter of the engine. The pH, temperature and dissolved oxygen in the culture were measured using appropriate probes (5083 T and 5120, Crison, Barcelona, Spain), connected to an MM44 control-transmitter unit (Crison Instruments, Spain), and data acquisition software (Labview, National Instruments) providing complete monitoring and control of the installation. The pH of the culture was controlled at 8.0 by on-demand injection of flue gas (from a diesel boiler), whereas temperature was not controlled; it ranged ±5ºC with respect to the daily mean air temperature, which varied from 12ºC in winter to 28ºC in summer. The raceway reactor was inoculated and operated in batch mode for one week, after which it was operated in semi-continuous mode at 0.2 day -1 at a culture depth of 0.15 m. Only samples from steady-state conditions were used. Evaporation inside the reactor was compensated by the daily addition of fresh water.

Analytical methods

The cultures were examined daily under a microscope, an Olympus CH20 (Olympus Corp., USA), to evaluate the cell status and to detect possible contamination. Images of the cultures were photographed for further use. Absorbance and turbidity were measured daily to monitor the evolution of the cultures. The dry weight biomass concentration (C b ) was measured by filtering 100 ml of culture through 1 µm filters and drying it at 80ºC in an oven over a 24 h period; this measurement was performed at the end of the culture. The dry weight biomass concentration values during the batch experiments were calculated from absorbance/turbidity measurements using the correlation obtained at the end of the batch culture. Biomass productivity was calculated as the product of the biomass concentration by the imposed dilution rate. The cell status was checked daily by measuring the chlorophyll fluorescence (F v /F m ) ratio with a fluorometer (AquaPen AP 100, Photon System Instruments, The Czech Republic). For this, the cells were adapted to the dark for 15 minutes prior to measurement. Absorbance in the visible range (400-700 nm) was measured daily using a double-beam Helios Alpha spectrophotometer and the extinction coefficient (Ka) was calculated by dividing the average absorbance value by the biomass concentration (Cb) and the cuvette's light path (d)): K a = Abs /(C b d). The average irradiance inside the culture (I av ) was calculated as a function of the irradiance at the surface (I o ), the biomass extinction coefficient (K a ), the biomass concentration (C b ) and the light path inside the reactor (d): 47

    p • C • K exp 1 • p • C • K I I b a b a light av    (1)
Because mean daily values were considered, irradiance during the light period (I light ) was used as the irradiance on the reactor surface to calculate the mean daily irradiance. The Quantum yield (Ψ E ) is defined as the amount of biomass generated by a unit of radiation (usually a mole of photons) absorbed by the culture. Since this represents the ratio of biomass generation to absorbed photon flux, it can be calculated using 48

Ψ E = P b F vol (2)
The photon flux absorbed through the reactor volume (F vol ) is calculated from the average irradiance on a culture volume basis using 48

F vol = I av • K a • C b (3)
The photosynthetic efficiency (PE) is the fraction of energy fixed into biomass as a function of the combustion heat of the biomass that was considered constant (Q b = 20 MJ/kg) 48

PE = P b • Q b F vol (5)
Freeze-dried biomass taken at the end of the batch culture was analysed. Lipids were determined gravimetrically from an extract obtained with chloroform:methanol (2:1) (v/v). 49 The protein content was determined using the modified Lowry method. 50 The moisture content was determined by weight losses after 24 h at 80ºC, whereas the ash content was determined by calcination at 550ºC for 6 h. The carbohydrate content of the biomass was determined as the difference remaining from 100% after taking away the protein, lipid and ash content.

RESULTS

CO 2 adsorption capacity of commercial zeolites: equilibrium properties and materials screening

The adsorption loadings in BEA, FAU, FER, ITQ-29, MFI, and MOR zeolites at near ambient conditions (298 K; and 1, 2 and, 10 bar) was obtained by GCMC simulation for three different typical flue gas mixtures (N 2 75%; CO 2 5%, 10%, and 15%; H 2 O at saturation conditions; and O 2 up to complete the mixture). Fig. 1 shows the gas uptakes as a function of the total pressure of the system. We can observe that the inclusion of water is almost negligible in all structures, as could be expected due to the pure-silica nature of the used materials. Competition of water with the rest of adsorbates is unfavored by the hydrophobic character of material and also due the fact that is the smallest molecule under study (kinetic diameter of around 2.6 Å). 51,52 Oxygen, is also almost displaced from adsorption by the other molecules, whatever is the concentration of CO 2 in the mixture.

Again, the size (i.e. kinetic diameter of 3.467 Å) and the low polarity of this molecule (quadrupole moment of ca. 0.39 D Å) 51,52 difficult its competition with the other gases. The overall performance strongly depends on the CO 2 fraction in the mixture, that is increased from 0.05 to 0.15 while the fraction of N 2 is fixed at 0.75. In the case of the lower concentration of CO 2 , N 2 prevails over CO 2 in almost all the zeolites. However, as soon as the CO 2 fraction is increased to 0.10, this molecule is able to displace N 2 from the main adsorption sites of the frameworks. Both molecules have similar kinetic diameters and the higher quadrupole moment of CO 2 probably makes the difference between them (4.30 D Å and 1.52 D Å, for CO 2 and N 2 respectively). This effect is less visible in FAU, the structure with the highest pore volume, because there is almost no competition for the available space at our pressure conditions. This is supported by the low total loading in this structure, being in the range of the other two structures with the lowest pore volume and surface area (i.e. MOR and FER). Another interesting exception is the low reduction in N 2 uptake in MOR while increasing CO 2 mixture fraction. As we say, CO 2 displaces N 2 from the main adsorption sites, but this is not the case of the additional adsorption sites in MOR, where CO 2 is rove? to not commensurate well. 30 CO 2 and N 2 Average Occupation Profiles (AOPs)

for the three different gas mixture compositions at the highest pressure in MOR zeolite (Fig. S7) reveals that while CO 2 is always adsorbed in the main channels, N 2 migrates from the main channels to the side pockets in which it almost does not compete with CO 2 . To make a deep insight in the performance in the different zeolites, Fig. 2a collects the CO 2 loadings from the computed adsorption isotherms for the mixture containing 10 % CO 2 in dry air. Among all the zeolites, MFI exhibits the highest uptake for all the pressure range. Loadings of 0.4, 0.7, and 1.2 mol kg -1 are obtained at 1, 2, and 10 bar of pressure, respectively. Adsorption values are not very high due the relatively low working pressures, but the adsorbed fraction of CO 2 (color graduation) is increased from 0.10 in the bulk mixture to more than 0.7, indicating a very high selective capture towards CO 2 . The AOPs of CO 2 in this structure (Fig. S8) show a strong adsorption of CO 2 in the intersections of the straight channels parallels to the y-axis and the zig-zag channels on the xz-plane.

Molecules seem to commensurate well in these adsorption sites, allowing this structure to show the best performance among the studied zeolites, both in terms of uptake and preferential adsorption. From Fig. S8 it can be also observed how zig-zag and parallel channels are progressively filled from the lowest to the highest pressure. The volumetric equipment used does not allow to discriminate the uptake corresponding to carbon dioxide in the mixture, for which the adsorption isotherm of synthetic air was also measured to estimate the contribution of nitrogen and oxygen to the adsorption of the mixture. As seen, the total amount of gas adsorbed for the mixture of 10% CO 2 in air at atmospheric pressure is about 15.3 g/Kg zeolite (0.35 mol/Kg), which is in good agreement with the amount computed for this zeolite at 1 bar. This experimental estimation is also in line with the IAST prediction for a mixture of 10% CO 2 in air evaluated from the experimental adsortpion isotherms of air and pure CO 2 (11.4-17.2 g/kg).

CO 2 adsorption capacity of best performing zeolite: PSA estimations

To compare the performance of each of the studied zeolites in a PSA industrial cycle, we have employed the so-called "Bed Capacity Factor" (BCF) to compare the PSA performance of each structure when using the Skarstrom cycle. 42 This parameter is defined as the adsorption capacity of the column utilized at the end of adsorption step (ADS in Fig. S3, incipient breakthrough of the adsorbate) under cyclic steady state operation relative to the maximum capacity of the column under feed gas conditions. For the same operating conditions, the lower this parameter is the better is the PSA performance because the process is able to remove a higher amount of heavy adsorbate from the light product (rich in weak adsorptive). The advantage of BCF parameter compared to others is that it considers simultaneously the effect of the most important variables that determine separation (working capacity, adsorption rate and selectivity). This is an advantage (apart from the possibility of treating a humid gas) because further drying of CO 2 is not necessary for using it in other applications.

Table 1. Performance parameters of the designed dual-PSA cycle

Biomass production and photosynthetic efficiency by microalgae and strain screening

The first step in the use of microalgae for CO 2 capture is the selection of the right strain. A lot of microalgae and cianobacteria strains has been investigated at this respect, in most of the cases performing batch cultures, others providing continuous light, and finally using non real flue gases. To obtain reliable figures for further scale-up processes the conditions at which the strains are evaluated must be as close as possible to that prevailing at outdoor. Here, the performance of ten previously reported microalgae/cyanobacteria has been evaluated. Fig. 3 shows that the different microalgae have largely different potential.

Scenedesmus was the most productive, with values up to 1.6 g/L•day, whereas Nostoc and Spirulina were the less productive, with productivities below 0.5 g/L•day (Fig. 3A).

Scenedesmus strain is widely reported under outdoor production conditions, including in CO 2 capture processes, as it has demonstrated itself to be robust and suitable for outdoor production, even in non-optimal raceway reactors or using wastewaters as the nutrient source 53,54 . In general cyanobacteria shows a lower performance that microalgae. These values are the maximal ones because they were obtained, although under simulated outdoor conditions, in a well-controlled and favourable environment. The obtained figures compare well with other previously reported. Thus, using Anabaena up to 1.0 g/L•day of captured CO 2 was obtained at laboratory scale, it being mainly accumulated at released exopolysaccharides. 55 In terms of photosynthetic efficiency (PE, Eq. ( 5)) an analogous trend is observed because the light provided was the same for all the experiments and the light utilization is proportional to the biomass productivity (Fig. 3B). Crucial information in this figure is the final values, as under optimal laboratory conditions the PE can be so high as 3.0 %, much higher than that found in higher plants of 1%. These figures justify the high potential of microalgae to efficiently use the sunlight to capture CO 2 and to transform it into valuable biomass. In this respect, it has been reported that up to 200 tn/ha•year of CO 2 could be captured by microalgae. To analyse the real figures about CO 2 capture and how it is transformed into valuable products the theoretical CO 2 fixation rate and biochemical composition of produced biomass were determined (Fig. S9 in the Supporting Information). Theoretical CO 2 fixation rate correspond to the amount of CO 2 fixed as biomass on the basis of biomass productivity and total carbon content of the biomass (ranging from 0.40 to 0.51% d.wt., data not shown). In addition to this value the net CO 2 fixation rate can be larger if the total carbon content of the biomass increases, but it is not modified too much if the cultures are operated at continuous mode, or if the CO 2 is additionally absorbed into the liquid as dissolved inorganic carbon. At laboratory scale these effects are not relevant. Hence, to consider only the net amount of CO 2 fixed as biomass is a valid approximate value. Results confirm that Scenedesmus is the most promising strain, showing values up to 2.5 g/L•day, much higher than that obtained when using Nostoc or Spirulina strains (Figure S9A). In terms of biochemical composition carbohydrates and proteins were the most relevant fractions, the lipids content being always lower than 20 %d.wt., except in the case of

Neochloris that shows a lipids content of 26 %d.wt. (Figure S9B). Neochloris is a small microalga that accumulates large amounts of lipids, up to 50% under non-growing conditions 56 . This strain has been widely reported as a potential biofuel source as it is even able to grow in wastewaters 57,58 . In the case of Scenedesmus the percentage of carbohydrates was really high, up to 53 %d.wt., but it was including higher in the case of Calothrix and Anabaena, with more than 70 %d.wt. of carbohydrates. In terms of proteins, the strain showing a higher protein content was Spirulina, up to 60%d.wt., whereas Anabaena and Calothrix shows the lowest contents, lower than 20 %d.wt., in spite that all of them are cyanobacteria. Similar biochemical composition to that here showed has been previously described for Chlorella vulgaris ( 59 ), Scenedesmus ( 60 ), and Neochloris ( 61 ). The different biochemical composition of the produced biomass indicate that each one of them could be used for different purposes as biofuels, biofertilizers, animal feed, etc. 62,63 However, the biomass value varies in the diverse applications so, to achieve a reliable process, it is necessary to identify a target market where the biomass value will be higher than its production cost. 19 As stated in the introduction, the choosing of the final strain to be used at large scale also depends on the value of the produced biomass and the economic yield of the process (Fig. 4). To determine these values a standard value of proteins (1 €/kg), lipids (0.6 €/kg) and carbohydrates (0.3 €/kg) has been considered, these values corresponding to the approximate price of these commodities. All the microalgae/cyanobacteria biomasses produced have an equivalent value, ranging from maximal value of 0.7 €/kg of Spirulina, to the minimum value of 0.4 €/kg of Anabaena (Fig. 4A). It is noticeable the high value of Neochloris because this strain have been widely reported as interesting for biodiesel production, 56 in addition to Nostoc which has been reported as a robust strain suitable to be produced at large scale. 64 However, Spirulina and Nostoc were some of the less productive strains. Multiplying the value of the biomass by the biomass productivity, i.e., the economic yield, is a more interesting criterion. The results that Scenedesmus is the most interesting strain in this respect, its economic yield being of 0.87 €/m 3 •day (Fig. 4B).

Biomass production and photosynthetic efficiency at outdoor conditions 20

Once the optimal strain has been selected, it was tested in real outdoor conditions, using a 100 m 2 pilot scale raceway reactor operated in continuous mode at 0.2 day -1 during six months from January to June at Almeria (Spain). On this time the solar radiation changes from 11 to 30 MJ/m 2 •day whereas the mean daily temperature ranged from 12ºC in winter time to 25ºC in summer time. In spite of large variations of solar radiation and temperature, not only along the days but also in each solar cycle, the cultures of Scenedesmus perform adequately, no large contamination problems existing and the culture being stable for long time (Fig. 5). Data shows as the biomass productivity increases from 10 to 30 g/m 2 •day from January to June mainly by the increase on solar radiation availability. On this time the photosynthetic efficiency did not change too much, a really high mean value of 2.0% being measured. These values confirm the adequacy of the selected strain to be used in large scale CO 2 capture processes. To determine the real CO 2 capture capacity, the mass flow of CO 2 entering to the reactor was measured, in addition to the net amount of CO 2 fixed into the biomass, and the CO 2 losses with the flue gases exhausting the reactor. The difference between the CO 2 inlet and the CO 2 outlet with the biomass and the flue gases was calculated as overall CO 2 losses. The results indicate that the CO 2 demand of the system increases when increasing the biomass productivity, due to the control system used to maintain the pH at its optimal value (Fig. 5b). The total CO 2 demand ranged from 27.6 to 76.7 g/m By comparing the performance of Anabaena cultures carried out in raceway, tubular photobioreactors and flat panels, the optimal value of 35 g/m 2 •day was achieved in flat panels reactors. 65 However, the scale-up of this technology is still a major issue in microalgae biotechnology field.

DISCUSSION

As mentioned in the introduction the purpose of this work is to analyze and compare the capability of CO 2 capture by a physicochemical means (adsorption in porous media) and by biological means (biomass production by microalgae). In this respect, not only the rate of CO 2 capture is of importance, but also the energy requirements of the process and the valorization of the final product.

As regards the former, the separation performance of the proposed dual-PSA process with the best performing zeolite MFI provides a figure of 8 kg m -3 bed h -1 , which is substantially higher that previously reported data by microalgae (0.04-0.25 kg m -3 broth h - 1 ) 66 and the data presented in this work: 0.00225 kg m -2 h -1 . On the other hand the energy requirement is lower than the one of amine scrubbing processes (0.37 kWh/kgCO 2captured = 1.3 MJ/kgCO 2captured ). 67 As regards the economic aspect, the obtained product (high purity CO 2 ) can be used in many applications, such as the obtention of carbon monoxide, methane or methanol.

With respect to the biological alternative, it must borne in mind that the CO 2 supply system must be accurately designed to avoid reemission of CO 2 to the atmosphere. Carbon photobioreactors 70 and 50 % in closed photobioreactors 71 have been determined. In both strategies, the consumption of CO 2 is a function of the design and the operation of the carbonation unit, and finally, of the mass transfer phenomena into the culture. In a different strategy the CO 2 can be provided dissolved into the culture medium by passing it by a previous carbonation unit, up to 2.0 g/L of total inorganic carbon being dissolved into the culture medium suitable to be consumed by Anabaena 72 . Recently the CO 2 capture efficiency in raceway reactors has been re-designed by including a sump into the reactor, and optimizing its design and gas/liquid flow rates. It was demonstrated that under optimal conditions de CO 2 transfer efficiency was up to 98% 73 .

On top of all these considerations, the energy consumption and cost of the biological process must also be analysed. In the case of energy, the major energy inlet on raceway reactors is the power required by the paddlewheel. To minimize the energy consumption, raceway reactors are build following some key rules, as a length to wide ratio of 10, using softer as possible materials, reducing the liquid velocity up to 0.2 m/s, and minimizing the presence of bends and other structural parts that disturb the flow along the channels [START_REF] Weissman | Design and analysis of microalgal open pond systems for the purpose of producing fuels: A subcontract report[END_REF] .

Recently the design of this type of reactors has been reviewed to minimize its energy consumption. In this respect a new Low Energy Algae Reactor (LEAR Patent EP2875724A1) has been patented. Thus, energy consumption in raceway reactors can be reduced from 20 to 1 W/m 3 , 21 or including below 1 W/m 3 if using LEAR system. During the operation of the 100 m 2 pilot scale raceway reactor the measured energy consumption was 2 W/m 3 , thus it being equivalent to 0.48 MJ/kg of CO 2 captured, which is substantially lower than the chemical (amines scrubbing) and physicochemical (zeolite adsorption) procedures.

In Fig. 6 the influence of biomass productivity and specific energy consumption on the raceway reactor into the specific energy consumption per kg of CO 2 captured is analized. It is confirmed that microalgae based processes have lower energy consumption that amines-based processes only when specific energy consumption of the reactor are lower than 20 W/m 3 and at biomass productivities are higher than 25 g/m 2 •day. When comparing with zeolites-based processes the microalgae have lower energy consumption only when operating at specific energy consumption in the raceway reactor lower than 2 W/m 3 and biomass productivities higher than 15 g/m 2 •day. Anyway, these figures show that the microalgae-based processes for CO 2 capture are in the same range of energy consumption than low energy demanding technologies as PSA with zeolites. In terms of cost, the biomass production cost in this type of raceway reactors can be reduced till 2.1 €/kg when using flue gases and minimum manpower (0.1 men/ha), it being equivalent to a CO 2 capture cost of 0.8 €/kg [START_REF] Acién | [END_REF] . This production cost is much higher than conventional price of industrial pure CO 2 , ranging from 0.1-0.2 €/kg. However, the price of microalgae biomass is much higher than of pure CO 2 , minimum values of 5 €/kg being reported 76 .

Considering this price for the biomass, the value of CO 2 contained into the biomass is 1.9 €/kg, much higher than estimated CO 2 capture cost of 0.8 €/kg. Thus, to achieve a suitable commercial process for CO 2 capture, it is necessary to produce valuable biomass otherwise the production cost will be higher than the CO 2 emission taxes 19 .

CONCLUSIONS

The alternative capabilities of a physicochemical (adsorption in porous media) and a biological process (biomass production by microalgae) to capture CO 2 from flue gases has been analysed, assessed and compared.

In connection to the physicochemical alternative, GEMC simulations and adsorption experiments demonstrate that commercial zeolite MFI is the best candidate to capture this gas due to the morphology and crystalline structure of this material. Numerical simulation of a dual PSA cycle suitable for industrial implementation confirms this finding and provide an estimated value for CO 2 capture of 8 kg m -3 bed h -1 and an energy compsuption of 0.987 MJ/Kg of captured CO 2 .

In connection to the biological alternative, it is demonstrated that microalgae-based processes for capturing CO 2 from flue gases can be performed, being reliable at real outdoor operation conditions for more than six months. The key factors determining the reliability of the process are the selection of adequate strains and technologies. From the up to ten microalgae/cyanobacteria strains evaluated, the fast growing and robust Scenedesmus almeriensis was the more productive, up to 0.06 kg m -3 broth h -1 . The production of this strain in a 100 m 2 pilot scale raceway reactor at real outdoor conditions was demonstrated, allowing to capture up to 54 gCO 2 /m 2 •day in average from January to June. The strategy of on-demand supply of CO 2 and optimal mass transfer capacity into the reactor allows to capture up to 2.58 kgCO 2 per kg of produced biomass, only 9.6% of the supplied CO 2 being lost to the atmosphere. Energy consumption of the process was estimated at 0.48 MJ/kgCO 2 , the unitary cost being 0.8 €/kg of CO 2 . The energy consumption is lower than the physicochemical process, but the cost is much high than regular price of pure CO 2 .

However, value of the microalgae biomass is much higher thus it being concluded that captured CO 2 have a value equivalent to 1.9 €/kg. These figures provide a realistic scenario about the potential application of microalgae to CO 2 capture related processes.

Although the major bottleneck of microalgae-based processes is the necessity of high sunlight and land availability, this technology can be an alternative for diffuse CO 2 emission from small industries and farms, among others. Physicochemical processes do not depend on ambient conditions and land availability but rely on a suitable use and management of the resulting stream of pure CO 2 obtained.

Section A. Details of interaction potentials for CO 2 , N 2 , O 2 and H 2 O

Atomic interactions were taken into account using electrostatic (Coulomb) and Van de Waals (Lennard-Jones) forces. For CO 2 , each interaction site corresponds to an atom center, with both partial charge and Lennard-Jones parameters assigned. 1 Central dummy pseudo-atoms (D), with partial charges but without mass or Lennard-Jones parameters, are defined for O 2 and N 2 to reproduce their first non-zero electrostatic moment. 2 The water molecule is described by the TIP5P/Ew model. 3 This model has already been proved as suitable for studying adsorption of water in zeolites. 4,5 This molecule is modeled by the O atom, the two H atoms and two extra dummy atoms (M) with tetrahedral site distribution, with the O at the center. There is only a single dispersive center at the O, and point charges are located at the H and M sites, the latter accounting for the negative partial charge of the oxygen atom. 3 Adsorbate-adsorbate cross van der Waals interactions are taken into account by Lorentz-Berthelot mixing rules. 6 In the case of zeolites, every Si atom is surrounded by four O atoms, and so the latter dominate the dispersive forces. The adsorbate-framework interactions are defined by those of the framework O atoms with the atoms of the adsorbed molecules. Since zeolites not always obey the Lorentz-Berthelot mixing rules for the adsorbate-framework interactions, Lennard-Jones parameters need to be independently adjusted. 1,7 To reproduce the interaction of CO 2 , N 2 and O 2 , and water with the zeolite, in this work we used parameters from Garcia-Sanchez et al., 1 Martin-Calvo et al., 8 and Castillo et al., 9 respectively. The set of charges for the framework atoms was also taken from Garcia-Sanchez et al. 1 All Lennard-Jones parameters and partial charges used in this work are collected in Table S1. 10 This structure has a 3-dimensional pore structure, with straight 12 membered-ring (MR) channels parallel to x-and y-axes with pore limiting diameters around 6-7 Å; and zig-zag 12MR pore path along the z-direction with a 5.6 Å limiting diameter.

Crystallographic positions of the atoms of zeolite MOR were taken from the work of Gramlich. 11 This zeolite is formed by parallel channels in the z-axis, with 12MR windows;

and additional adsorption sites in the y-axis, so called side pockets. Channels and pockets can be observed in the peaks in the Pore Size Distribution (PSD) in Fig. S1 at ca. 6 and 4.2

Å respectively. Pockets are accessible from the main channels only for small molecules. 12 FER shows a 2-dimensional intersected system of channels of 4.7 Å (10-membered rings along z-axis) and 3.4 Å (8-membered rings along y-axis) limiting diameters. 13 10-members rings also configure main channels of MFI zeolite (x-axis), which are intersected by zig-zag secondary channels leading to a 3-dimensional system with limiting diameters around 4.5-4.7 Å. 14 The two last zeolites under study, ITQ- q Molec. Sim. [ mol kg -1 ] FER q IAST [ mol kg -1 ] FER q Molec. Sim. [ mol kg -1 ] ITQ-29 q IAST [ mol kg -1 ] ITQ-29 q Molec. Sim. [ mol kg -1 ] MFI q IAST [ mol kg -1 ] MFI q Molec. Sim. [ mol kg -1 ] MOR q IAST [ mol kg -1 ] MOR Partial Pressure [ Pa ] q Molec. Sim. [ mol kg -1 ] BEA q IAST [ mol kg -1 ] BEA q Molec. Sim. [ mol kg -1 ] FAU q IAST [ mol kg -1 ] FAU Partial Pressure [ Pa ] Table S6. Fitted Langmuir parameters in MFI structure.

Figure 1 .

 1 Figure 1. Adsorption loading of N 2 (squares), CO 2 (circles), O 2 (triangles), and H 2 O (diamonds) in BEA, FAU, FER, ITQ-29, MFI, and MOR zeolites at room temperature and 1,2, and 10 bar of pressure. The color line indicates the fraction of CO 2 in the gas mixture.

Figure 2 .

 2 Figure 2. (A) Computed CO 2 adsorption loadings in BEA (squares), FAU (circles), FER (circles), ITQ-29 (asterisks), MFI(triangles), and MOR(diamonds) zeolites at room temperature and 1, 2, and 10 bar of pressure loadings for a mixture containing 10 % CO2 in dry air. The color code shows the CO 2 adsorbed fraction. (B) Experimental adsorption isotherms for MFI zeolite at room temperature for pure CO 2 , synthetic air and a mixture containing 10 % CO 2 in dry synthetic air. []

  For a single PSA cycle at isothermal conditions we obtained the following BCF values: MFI = 0.21; BEA= 0.53; FER = 0.56; MOR = 0.68; ITQ-29 = 0.80; FAU = 0.99. These results are in close agreement with the previously obtained results from GCMC simulations (Section 3.1) and confirms that MFI offers quite better performance than the rest of structures for CO 2 capture and separation from the flue gas.On these grounds, the MFI zeolite is chosen to simulate the PSA dual cycle with three equalization steps at adiabatic conditions. As mentioned above, this type of arrangement improve the yield of CO 2 separation in industrial processes. The design specifications of the dual-PSA cycle have been defined as a CO 2 purity in the heavy product above 95% and CO 2 recovery above 90% (calculated as global results for the two coupled cycles). The feed gas velocities of both cycles have been used as input variables to achieve the desired design specifications, resulting in a feed gas velocity of 0.0452 m s -1 for the rectifying cycle (PSA I) and 0.11 m s -1 for the stripping cycle (PSA II). A flowsheet with the molar flow rates and stream compositions of the designed dual cycle is shown in Fig.S4b. The performance parameters of each individual cycle and the global ones for the dual cycle are presented in

19

 19

Figure 3 .

 3 Figure 3. Biomass productivity (A) and photosynthetic efficiency (B) of microalgae strains evaluated at laboratory scale.

Figure 4 .

 4 Figure 4. Value of the biomass and economic yield of the system of different strains tested at laboratory conditions.

Figure 5 .

 5 Figure 5. Variation of biomass productivity and photosynthetic efficiency (A), in addition to CO 2 inlet and outlet streams, of outdoor continuous cultures of Scenedesmus almeriensis in a 100 m 2 pilot scale raceway reactor located in Almeria (Spain).

  dioxide can be supplied to microalgae cultures by (a) continuous bubbling or (b) ondemand injection. With continuous bubbling of flue gases, the medium becomes acidic and maximum CO 2 use efficiencies of only 8.1 % 68 and 4.2 % 69 have been reported. With ondemand injection of flue gases, a maximum CO 2 use efficiency of 32.8 % in open

Figure 6 .

 6 Figure 6. Variation of energy consumption of microalgae based processes as a function of biomass productivity and specific energy consumption of the reactor.

Fig. S2 . 5 a

 S25 Fig. S2. Pore-size distributions of the zeolites under study.

9 - 46 KH0 9 -

 9469 H O2, kJ mol -1 15.H2O, mol kg -1 Pa -1 3.621•10 -9 b0 H2O, Pa-1 1.448•10 -H H2O, kJ mol -1 7.25

Figure S3 .Figure S4 .

 S3S4 Figure S3. PSA cycle for comparing separation performance. F = feed gas, L = light product, T = tail gas, PH = high pressure, PL = low pressure, ADS = feed gas adsorption, BD = blowdown, RP = receive purge, PR = pressurization, uF = feed gas velocity in the adsorption step, uP = feed gas velocity in the purge step.

  ADS ADS DEQ1 DEQ2 DEQ3

Figure S5 . 40 Figure S6 .

 S540S6 Figure S5. Comparison between pure adsorption isotherms at 298 K obtained by molecular simulation and fitted with Langmuir model.

Table 1 .

 1 A CO 2 productivity of 8.24 kg/m 3 /h is estimated. The energy requirement for evacuation steps has been calculated assuming isoentropic compression with efficiency of 60%. From Fig.S4b, it is observed that practically dry CO 2 is obtained as final product.

  2 •day. This CO 2 was mainly consumed by the biomass, their values ranging from 17.5 to 49.3 g/m2 •day. The larger amount of CO 2 supplied with respect to the net amount fixed into the biomass was due to the efficiency of the CO 2 supply system. Thus, CO 2 losses by non-absorption of CO 2 contained into the flue gases injected ranges from 1.4 to 4.8 g/m 2 •day. These values are really minor when comparing with total CO 2 supplied, indicating the adequate performance of the CO 2 gas supply system. However, still a large fraction of CO 2 was lost, ranging from 8.7 to 22.6 g/m 2 •day. These losses can be due to decarbonisation into the entire raceway reactor or carbon outlet with the outlet culture broth when harvesting. Anyway, the total amount of CO 2 demanded by the system was 54 g/m 2 •day, equivalent to 197 t/ha•year. This means that the CO 2 demand to biomass productivity ratio is 2.58, instead of the 1.83 value theoretically obtained if considering the basic equation of photosynthesis. This is an important fact considering CO 2 emissions at ground level or the increase of inorganic carbon concentration in the exhausted water for its final disposal. On average, the CO 2 fixation into the biomass represent 64.0% of the total CO 2 inlet, whereas CO 2 losses with the exhaust gas represent 9.6% of the total CO 2 inlet, then the remaining CO 2 losses representing up to 26.4% of total CO 2 inlet. Although raceway reactors are the most suitable for CO 2 capture-related processes other technologies has been previously studied.

Table S1 .

 S1 Lennard-Jones parameters and partial charges of the adsorbates and the adsorbents

	Section B.
	Atom 1	Atom 2	ε/kB (K)	σ (Å)	Charge (e -)
	Adsorbed Molecules
	C(CO2)	C(CO2)	29.933	2.745	0.651
	O(CO2)	O(CO2)	85.671	3.017	-0.326
	O(O2)	N(O2)	53.023	3.045	-0.112
	D(O2)	D(O2)	-	-	0.224
	N(N2)	N(N2)	38.298	3.306	-0.405
	D(N2)	D(N2)	-	-	0.810
	O(H2O)	O(H2O)	89.516	3.097	-
	H(H2O)	H(H2O)	-	-	0.241
	M(H2O)	M(H2O)	-	-	-0.241
	Zeolite
	O(zeo)	O(zeo)	-	-	-0.393
	Si(zeo)	Si(zeo)	-	-	0.786
	Adsorbed Molecules -Zeolite
	C(CO2)	O(zeo)	37.595	3.511	-
	O(CO2)	O(zeo)	78.98	3.237	-
	O(O2)	O(zeo)	60.189	3.129	-
	D(O2)	O(zeo)	-	-	-
	N(N2)	O(zeo)	60.580	3.261	-
	D(N2)	O(zeo)	-	-	-
	O(H2O)	O(zeo)	13.710	3.377	-
	H(H2O)	O(zeo)	-	-	-
	M(H2O)	O(zeo)	-	-	-

Morphological and structural description of the zeolites BEA

  , MOR, FER, and MFI are zeolites with a structure consisting of interconnected channels with different directionality. Crystallographic positions of zeolite BEA were taken from Newsam et al.

Table S4 .

 S4 Fitted Langmuir parameters in the studied structures at 298 K

		). BEA: 1508; FAU: 1342; FER: 1838; ITQ-29: 1433; MFI: 1796; MOR:
	1711.
	Gas/Structure	KH, mol kg -1 Pa -1	b, Pa -1
	N2/BEA	1.693•10 -6	4.960•10 -7
	CO2/BEA	1.946•10 -5	3.679•10 -6
	O2/BEA	1.324•10 -6	2.873•10 -7
	H2O/BEA	1.096•10 -7	2.193•10 -8
	N2/FAU	9.132•10 -7	1.338•10 -7
	CO2/FAU	4.844•10 -6	-1.006•10 -6
	O2/FAU	7.853•10 -7	5.259•10 -8
	H2O/FAU	1.565•10 -7	1.565•10 -12
	N2/FER	1.280•10 -6	1.004•10 -6
	CO2/FER	1.775•10 -5	1.559•10 -5
	O2/FER	1.088•10 -6	7.494•10 -7
	H2O/FER	3.972•10 -8	3.972•10 -8
	N2/ITQ-29	1.366•10 -6	2.882•10 -7
	CO2/ITQ-29	1.164•10 -5	1.018•10 -6
	O2/ITQ-29	1.146•10 -6	1.800•10 -7
	H2O/ITQ-29	9.560•10 -8	9.560•10 -11
	N2/MFI	2.730•10 -6	1.234•10 -6
	CO2/MFI	5.393•10 -5	1.982•10 -5
	O2/MFI	2.003•10 -6	7.387•10 -7
	H2O/MFI	6.703•10 -8	2.234•10 -8
	N2/MOR	1.984•10 -6	7.214•10 -7
	CO2/MOR	1.226•10 -5	4.756•10 -6
	O2/MOR	1.573•10 -6	4.863•10 -7
	H2O/MOR	1.058•10 -7	2.645•10 -8

b Calculated with AspenPlus program

Table S5 .

 S5 Comparison between the multicomponent equilibrium data calculated from molecular simulation and IAST method.

	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O
	75000	5000	16834	3166	0.118436	0.086011	0.020923	0.000329	0.119043	0.086088	0.021040	0.000333	0.067088	0.023790	0.013026	0.000456	0.067759	0.023930	0.013109	0.000499
	150000	10000	36834	3166	0.223561	0.165428	0.043583	0.000330	0.223797	0.165456	0.043712	0.000316	0.132695	0.047887	0.028460	0.000468	0.134065	0.048255	0.028529	0.000498
	75000	10000	11834	3166	0.116033	0.171125	0.014443	0.000344	0.116627	0.171118	0.014526	0.000327	0.067263	0.047954	0.009133	0.000486	0.067838	0.048090	0.009226	0.000501
	150000	20000	26834	3166	0.214625	0.325900	0.030756	0.000335	0.215284	0.326285	0.030820	0.000306	0.132779	0.097111	0.020678	0.000468	0.134377	0.097450	0.020860	0.000501
	75000	15000	6834	3166	0.113967	0.255141	0.008233	0.000353	0.114293	0.254837	0.008230	0.000322	0.067293	0.072627	0.005289	0.000471	0.067917	0.072484	0.005327	0.000502
	150000	30000	16834	3166	0.206180	0.481186	0.018629	0.000364	0.207304	0.481099	0.018721	0.000297	0.132533	0.147686	0.012995	0.000497	0.134692	0.147613	0.013129	0.000503
	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O
	75000	5000	16834	3166	0.099396	0.053275	0.018837	0.000312	0.099083	0.053318	0.018713	0.000301	0.167541	0.216426	0.028325	0.000199	0.167999	0.216482	0.028175	0.000181
	150000	10000	36834	3166	0.191907	0.104707	0.040268	0.000328	0.191721	0.104997	0.039849	0.000297	0.286234	0.377983	0.053509	0.000181	0.283747	0.377118	0.053059	0.000157
	75000	10000	11834	3166	0.098672	0.106784	0.013208	0.000317	0.098347	0.106884	0.013064	0.000301	0.153918	0.405445	0.018412	0.000193	0.154163	0.406260	0.018331	0.000168
	150000	20000	26834	3166	0.187829	0.210007	0.028997	0.000334	0.188951	0.210075	0.028680	0.000296	0.249821	0.681169	0.034581	0.000184	0.245600	0.680491	0.034007	0.000139
	75000	15000	6834	3166	0.097804	0.160497	0.007562	0.000340	0.097619	0.160519	0.007483	0.000300	0.142975	0.574388	0.009986	0.000190	0.142298	0.575397	0.009838	0.000157
	150000	30000	16834	3166	0.183302	0.313249	0.017854	0.000341	0.186236	0.313216	0.017769	0.000295	0.219974	0.921248	0.019260	0.000178	0.215942	0.921512	0.019033	0.000125
		Partial Pressure [ Pa ]
	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O	N2	CO2	O2	H2O
	75000	5000	16834	3166	0.081683	0.079185	0.015713	0.000126	0.081931	0.079435	0.015748	0.000106	0.138624	0.056895	0.024861	0.000306	0.137033	0.057128	0.024479	0.000316
	150000	10000	36834	3166	0.143100	0.136988	0.030600	0.000127	0.142960	0.136122	0.030353	0.000091	0.254459	0.105702	0.050046	0.000292	0.253587	0.105431	0.049914	0.000296
	75000	10000	11834	3166	0.076691	0.147882	0.010456	0.000122	0.076838	0.147836	0.010411	0.000099	0.136637	0.111903	0.017171	0.000312	0.134517	0.112089	0.016901	0.000311
	150000	20000	26834	3166	0.129291	0.243012	0.020156	0.000120	0.128597	0.241786	0.020010	0.000080	0.245969	0.203359	0.035452	0.000299	0.245127	0.203595	0.035227	0.000288
	75000	15000	6834	3166	0.072479	0.208302	0.005675	0.000127	0.072413	0.207475	0.005674	0.000092	0.135144	0.165497	0.009815	0.000314	0.132094	0.165006	0.009577	0.000306
	150000	30000	16834	3166	0.117906	0.328434	0.011643	0.000118	0.117156	0.326738	0.011494	0.000072	0.239163	0.295514	0.021779	0.000301	0.237230	0.295223	0.021424	0.000280

ACKNOWLEDGEMENTS

This study was carried out with the financial support of Junta de Andalucía, grant FQM 1851 and the company, SETEC. We are grateful for the practical assistance kindly given by the staff of the Las Palmerillas Experimental Station, part of the Cajamar Foundation.

Potential of CO 2 capture from flue gases by physicochemical and biological methods: a comparative study -Supporting Information

Section C. Details of PSA simulations PSA simulations have been carried out with PSASIM software. 17 Parameters of the simulation are collected in Table S3. PSA numerical simulations were performed using the cycle shown in Fig. S3 (adiabatic conditions) to discriminate between the separation performance of the different zeolites. Subsequently, a dual cycle (Figure S4) was used to improve the yield of CO 2 zeolite for the MFI zeolite only.

The multicomponent adsorption isotherms for the PSA simulations were obtained by applying the IAST method to the pure component adsorption isotherms, previously obtained by GCMC simulations. Isotherms were fitted with the Langmuir model. A comparison between the pure component adsorption isotherms and the fitted ones is shown in Fig. S5. The fitted Langmuir parameters are shown in Table S4. A comparison between the multicomponent equilibrium data calculated with both methods is shown in Table S5.

The introduction a correction factor for the adsorbed concentration of CO 2 calculated from IAST method ranging between 0.93 and 1.02 was necessary to accurately predict multicomponent equilibrium data obtained from molecular simulation. The good agreement between the obtained results after applying the correction can be observed in the Table S5.

Supplementary results


Juan José

Viña Mediavilla

Begoña Fernández Pérez

Julia Ayala Espina

Maria Concepcion Conchi

Ovin Concepcion

Ania

Ania Ovin

Del Eficacia

Permanganato Potásico

Viña Mediavilla1

Begoña Fernandez
email: fernandezbegona@uniovi.es

Julia Ayala Espina1

Conchi O Ania2
email: conchi.ania@cnrs-orleans.fr

EFICACIA DEL PERMANGANATO POTÁSICO EN LA DEGRADACIÓN DE CIANURO Y TIOCIANATO EN AGUAS RESIDUALES MINERAS

Keywords: Cianuros, Tiocianatos, Contaminación ambiental, Cyanides, thiocyanates, potassium permanganate, acid mine wastewater

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

RESUMEN

El objetivo de este trabajo se centra en evaluar la viabilidad de la utilización de permanganato de potasio como método eficaz de detoxificación de aguas residuales procedentes del sector de la minería aurífera conteniendo cianuros y tiocianatos. Para ello se evaluaron las condiciones óptimas (e.g. concentración de oxidante, tiempo de reacción) para la degradación simultanea de ambas especies cianuradas, comparando la eficiencia de oxidación con la de aguas sintéticas. Los resultados indican que el permanganato de potasio es un agente oxidante eficaz y confiable para la eliminación de cianuro de aguas residuales de la minería aurífera, si bien la eficiencia de degradación de tiocianatos es mucho menor. Asimismo, la oxidación parcial de tiocianato da lugar a la aparición de una concentración residual de cianuros en el agua residual tratada. Esto hace necesario aplicar un segundo método de oxidación para la eliminación total de las especies cianuradas.

INTRODUCCIÓN

El cianuro y el tiocianato son dos compuestos tóxicos que se encuentran frecuentemente en las aguas residuales del procesamiento de minerales de oro y de la fabricación de coque para la producción de acero (Vicente, 2003;[START_REF] Logsdon | The Management of Cyanide in Gold Extraction[END_REF]. El tiocianato, que también se forma biológicamente a partir de la detoxificación del cianuro, es menos tóxico pero más estable que este último y, por tanto, más difícil de degradar [START_REF] Gould | A critical review on destruction of thiocyanate in mining effluents[END_REF].

Por otra parte, las reglamentaciones medioambientales en un gran número de países (incluyendo normativa española) limitan los niveles de cianuro en agua potable a valores inferiores a 0,07 µg/l [START_REF] Oms | Organización Mundial de la Salud: Cyanide in drinking-water. Documento de referencia para la elaboración de las Guías de la OMS para la calidad del agua potable[END_REF]. No obstante, no existe legislación directa acerca de la liberación de tiocianato en el medio ambiente, aunque varias agencias reguladoras han publicado directrices de vigilancia de concentración de tiocianato en agua [START_REF] Dash | Removal of cyanide from water and wastewater using granular activated carbon[END_REF] basándose en estudios sobre la toxicidad directa o indirecta de ambos compuestos en los vertebrados (problemas respiratorios, mortalidad).

Los altos precios del oro desde principios de la década de 1980 han dado como resultado un aumento en su producción, haciendo minas rentables aquéllas que habían dejado de serlo. El método más común de extracción de oro de sus minerales en la industria es la lixiviación con cianuro (Ballester, 2003), dado que la recuperación del oro de minerales refractarios que contienen minerales complejos no es un proceso simple y la cianuración presenta los mejores resultados, si bien es también un método ambientalmente peligroso. De acuerdo con la literatura, las concentraciones de cianuros y tiocianatos en efluentes de concentradores de mineral de oro pueden variar entre 40-700 mg/l, respectivamente (Logsdom, 2004[START_REF] Soto | Regeneration of cyanide by ozone oxidation of thiocyanate in cyanidation tailings[END_REF].

Se han estudiado diferentes técnicas de degradación para el tratamiento de corrientes contaminadas con cianuro y tiocianato [START_REF] Kuyucaka | Cyanide and removal options from effluents in gold mining and metallurgical processes[END_REF]Botz, 2016). Los tratamientos naturales, biológicos u oxidativos son los más ampliamente utilizados [START_REF] Dabrowski | Photooxidation of dissolved cyanide using TiO2 catalyst[END_REF][START_REF] Budaev | Removal of Thiocyanates by Persulfates from Gold Mine Wastewater[END_REF]. En el caso de los tiocianatos, menos estudiados, el tratamiento biológico resulta, en algunos casos, una solución simple y la opción más económica [START_REF] Pérez | Degradación biológica de tiocianato; Tecnología del agua[END_REF][START_REF] Medina | The thiocyanate degradation by fungi isolated from mining environments and evaluation of degradative capacity[END_REF] Sin embargo, la aplicación del tratamiento biológico se limita a bajas concentraciones de tiocianato; por otra parte, estos sistemas de tratamiento no son estables porque la combinación de ambas especies presenta una alta capacidad de inhibición de las bacterias necesarias para degradar los contaminantes (Douglas 2012, Mekuto 2017).

La degradación de cianuros ha sido más ampliamente estudiada, y se ha propuesto un gran número de métodos de eliminación (Botz, 2016). Entre los procesos destructivos más utilizados destacan los métodos oxidativos; los procesos Degüssa (mediante la utilización de peróxido de hidrógeno) (Boltz 2002) e INCO (con utilización de SO 2 ) destacan por ser los métodos empleados mayoritariamente en las plantas mineras actuales. No obstante presentan el inconveniente de un alto consumo de reactivos debido a la reacción con otros compuestos presentes en las aguas. Las plantas mineras se ven obligadas a tratar el agua contaminada varias veces con el mismo proceso, o al uso de métodos en tándem para lograr los límites requeridos por las legislaciones medioambientales vigentes.

Los efluentes de desecho de estas minas contienen, además de cianuros, elevadas concentraciones de tiocianatos que se envían a los estanques de relaves, para lograr la degradación natural de dichos compuestos cianurados, otros compuestos químicos presentes y metales, con el consiguiente peligro que entraña en el entorno por posibles fallos en las instalaciones de contención, dado que el proceso es a muy largo plazo.

Es poco probable que las preocupaciones sociales y medioambientales sobre esta minería que utiliza cianuro para la extracción de oro de sus menas se disipen en un futuro cercano. La combinación de imágenes negativas inherentes al uso del cianuro, así como los problemas medioambientales asociados con este tipo de minería, hace que este proceso continúe generando críticas, por lo que se hace necesario la búsqueda de un método que permita la eliminación efectiva de ambos contaminantes.

El permanganato de potasio (KMnO 4 ) es un oxidante fuerte ampliamente utilizado para el tratamiento del agua. Con este fin, se utilizó por primera vez en 1910 para el tratamiento del agua en Londres [START_REF] Pizzi | Principles and Practices of Water Supply Operations. Water Treatment[END_REF] Los estudios realizados por la Universidad de Florida muestran las propiedades bactericidas del permanganato de potasio [START_REF] Marecaux | Effects of Potassium Permanganate on the Sailfin Molly, Poecilia Latippinna, at Varying Salinity Levels[END_REF]. Sin embargo, no fue hasta 1970 en el que KMnO 4 se utilizó por primera vez como agente oxidante [START_REF] Medialdea | Permanganato potásico: Un potente y versátil oxidante, Ingenierıa Química[END_REF]. En la actualidad, KMnO 4 se usa comúnmente en la industria para la seguridad de la salud ambiental.

Nuestros estudios previos han demostrado que se comporta como un agente de desintoxicación efectivo del cianuro (Fernandez 2007;[START_REF] Sancho | Uses of the potassium permanganate to eliminate copper cyanide from waste water resulting from a lixiviation plant in a gold mine (I)[END_REF] con excelentes resultados en aguas residuales sintéticas y naturales de la extracción de oro. Para lograr una reacción de oxidación segura y efectiva debe llevarse a cabo en condiciones fuertemente alcalinas de pH 12-14 (e.g., potencial redox del par MnO 4 -/Mn 2+ en medio básico de 0.82 V). En estas condiciones, el KMnO 4 puede transformar el cianuro en cianato y otros derivados con menos toxicidad.

El objetivo de este trabajo es evaluar la viabilidad y eficacia de la utilización de KMnO 4 para el tratamiento de aguas residuales de proceso de la industria minera de extracción de oro, con altas concentraciones de cianuro y tiocianato.

MATERIALES Y MÉTODOS

Aguas residuales mineras

Se estudiaron cuatro fuentes de agua residual con concentraciones diferentes, procedentes todas ellas de una instalación minera local. La empresa emplea el proceso de cianuración CIL (Carbon In Leach) para la disolución del oro de granulometría muy fina en la mena, de acuerdo con la reacción (1) [START_REF] Elsner | Observations on the behavior of pure metals in an aqueous solution of cyanide[END_REF]:

4 Au + 8 Na (CN) + O 2 + 2 H 2 O ⇒ 4 NaAu (CN) 2 + 4 NaOH (1)
De este modo se genera una pulpa residual que se envía a un tanque de detoxificación con anhidro sulfuroso líquido, utilizando tecnología INCO (Yarar, 2002;[START_REF] Fernández | Desarrollo de un Nuevo Método para la Eliminación de Cianuro de Aguas Residuales de Mina[END_REF] previamente a su envío a la presa de residuos y su posterior recirculación como Agua de Proceso a la planta de tratamiento.

Las aguas utilizadas para este trabajo proceden de cuatro ubicaciones diferentes de la instalación: Agua del tanque de tratamiento de cianuración (CIL), Aguas de proceso (AP), procedentes de la planta de tratamiento metalúrgico de la instalación, Aguas de proceso pretratadas (APT), procedentes de la detoxificación de las aguas del tanque CIL con el proceso INCO y Aguas de drenaje (AD) de la balsa de contención. Esta selección de aguas de distintas corrientes ha permitido evaluar la eficacia del método en un amplio abanico de concentraciones de cianuro, con valores de 312, 40-50,15 y 1.9 ppm de cianuro para las aguas CIL, AP, APT y AD, respectivamente. La concentración de tiocianatos de las distintas aguas se encuentra en valores comprendidos entre 300-600 ppm.

Disoluciones Sintéticas

Con objeto comparativo, se utilizaron disoluciones sintéticas de cianuros y tiocianatos con concentraciones de 100, 200, 400 y 500 ppm para los cianuros, y entre 50 y 200 ppm para los tiocianatos. Las disoluciones se prepararon disolviendo cianuro y tiocianato potásico en agua destilada. El pH resultante de estas disoluciones fue de 8.

Procedimiento de oxidación

Los ensayos de oxidación se realizaron en condiciones básicas en todos los casos, con un pH de 12 obtenido mediante la adición de óxido de calcio.

Tras alcanzar el valor de basicidad requerido, se pusieron en contacto las disoluciones de permanganato potásico (concentración inicial de 2,5% en peso) y la disolución sintética o el agua residual mediante agitación durante 20 minutos [START_REF] Fernández | Desarrollo de un Nuevo Método para la Eliminación de Cianuro de Aguas Residuales de Mina[END_REF]. Las muestras se filtraron para eliminar los lodos generados, y posteriormente se analizó la concentración de ambas especies cianuradas remanente en disolución. Se utilizaron diferentes relaciones másicas KMnO4:CN (entre 2 y 5) y KMnO4:SCN (entre 1 y 7). Para el estudio con aguas sintéticas se trabajó con muestras de 50 ml de disolución. En el caso de los ensayos con las aguas reales se utilizaron tanques de 4 litros de capacidad, a los que se les aplicó un procedimiento similar.

Determinación de concentraciones de cianuros y tiocianato

Se utilizaron varias técnicas analíticas para el control tanto de los compuestos cianurados (cianuro y tiocianato) como de los compuestos intermedios generados durante el tratamiento. La concentración de cianuros en aguas reales se determinó mediante el método del ácido pícrico [START_REF] Fernández | Desarrollo de un Nuevo Método para la Eliminación de Cianuro de Aguas Residuales de Mina[END_REF]. Se trata de un método relativamente sencillo y adecuado para un amplio rango de concentraciones y ampliamente utilizado en las instalaciones mineras auríferas. Su fundamento es el desarrollo del color de la solución a analizar, mediante la acción del ácido pícrico en presencia de níquel, y un calentamiento de la solución "al baño María" durante 30 minutos. La medida de la especie coloreada generada se llevó a cabo en un espectrofotómetro Brickman fijando la longitud de onda a 520 nm.

Paralelamente se utilizó un método de análisis de inyección en flujo (FIA, Flow Injection Analysis) para la determinación de cianuros totales en las aguas

RESULTADOS Y DISCUSIÓN

El permanganato de potasio es un oxidante fuerte ampliamente utilizado para el tratamiento del agua. Nuestros estudios previos han demostrado que en condiciones fuertemente alcalinas de pH 12-14, se comporta como un agente de desintoxicación efectivo de cianuro (Fernandez 2007;[START_REF] Sancho | Uses of the potassium permanganate to eliminate copper cyanide from waste water resulting from a lixiviation plant in a gold mine (I)[END_REF] con excelentes resultados en aguas residuales sintéticas y naturales de la extracción de oro [START_REF] Ordiales | Potassium Permanganate as an Alternative for Gold Mining Wastewater Treatment[END_REF]. De este modo se evita la generación de compuestos incluso más tóxicos como ocurre con el gas cianógeno (Vella, 1996). En estas condiciones, el KMnO 4 puede transformar el cianuro en cianato y otros derivados con menos toxicidad, de acuerdo con las siguientes reacciones:

2 MnO 4 -+ 3CN -+ H 2 O → 2 MnO 2 + 3 CON -+ 2 OH - (2) 2CNO -+ 4OH -→ 2CO 2 + N 2 + 2H 2 O (3) CNO -+ 2H 2 O → NH 4 + + CO 3 2- (4) 2NH 4 + + 3O 2 2NO 2 -+4H + +2H 2 O (5) 2NO 2 -+O 2 2NO 3 - ( 6
)
Con objeto de validar la eficacia de la utilización del KMnO 4 como oxidante para aguas con diferentes concentraciones de cianuros y tiocianatos, e realizaron ensayos con aguas sintéticas y con aguas procedentes de diferentes áreas de una instalación minera con concentraciones variables de cianuro.

Aguas sintéticas

Inicialmente se realizaron ensayos con aguas sintéticas con distintas concentraciones de cianuro de potasio en solución, para corroborar las condiciones óptimas de tratamiento establecidas previamente en la bibliografía para la aplicación de este método oxidativo. La figura 1 presenta la tasa de eliminación de cianuros para diferentes relaciones másicas KMnO4:CN en una disolución de 200 ppm de concentración inicial. Como se puede apreciar, al aumentar la cantidad de permanganato aumenta la degradación de cianuros, alcanzándose valores cercanos al 90% de eliminación para la mayor relación másica empleada (5:1 de KMnO4:CN). El hecho de no obtenerse una degradación completa se debe a que en estas condiciones se trabaja en defecto de agente oxidante (en todos los casos se produjo un consumo completo permanganato), por lo que sería necesario aumentar la dosis de permanganato para obtener un rendimiento del 100 %.

En la tabla 1 se recogen los resultados obtenidos para distintos ensayos utilizando la relación másica de 5:1 de KMnO4:CN y variando la concentración de cianuros entre 500 y 100 ppm. Se recogen los porcentajes de degradación de cianuros así como los intermedios generados durante el proceso oxidativo.

Los resultados muestran que la tasa de degradación aumenta a medida que desciende la concentración de cianuro en la disolución inicial. Igualmente, la cuantificación del agente oxidante confirmó un exceso de permanganato solamente en el caso de la disolución de 100 ppm CN-de concentración inicial, para la cual se obtuvo un rendimiento del 99%.

No se detectaron cianatos en ninguna de las disoluciones medidas en estas condiciones experimentales, lo que indica que la hidrólisis de este compuesto para generar iones amonio es muy rápida, tal como ha sido reportado para otros sistemas de oxidación [Oulego, 2014;xxxxGO, 2014;].

Asimismo, se detectaron nitritos y nitratos, lo que indica la oxidación posterior de iones amonio generados en la hidrolisis de cianato, favorecidas por la presencia de permanganato y de oxígeno en solución.

En la figura 2 se presentan los resultados de los ensayos realizados con aguas sintéticas con 200 ppm de KSCN y diferentes relaciones másicas de KMnO4:SCN -. Se puede observar que el porcentaje de eliminación de tiocianatos aumenta con la cantidad de permanganato empleadas; no obstante, el rendimiento final de degradación apenas supera el 30%, incluso para las relaciones másicas más elevadas.

En la tabla 2 se recogen los intermedios generados durante el tratamiento de las disoluciones sintéticas de tiocianato de concentraciones iniciales entre 50 y 200 ppm, con una relación másica KMnO4:SCN -. de 3:1. En este caso se observa la aparición de concentración de cianuros, cianato, sulfatos y varias especies oxidadas de nitrógeno (amonio, nitratos y nitritos). La presencia de cianuros como intermedio de degradación de tiocianatos en disoluciones sintéticas indica que el mecanismo de oxidación procede a través de la reacción:

6 MnO 4 -+ SCN -+ 8OH -→ 6 MnO 3 2-+ SO 4 2-+ CN -+ 4H 2 O (7)
seguida de las reacciones anteriormente señaladas para la degradación de cianuro. Un mecanismo similar ha sido propuesto para la oxidación de tiocianato a partir de otros oxidantes (ozono, peróxido de hidrógeno).

Asimismo, es interesante destacar que en el caso de la oxidación de tiocianato, al contrario de lo que se observó para el cianuro, es posible detectar cianato antes de su hidrólisis (Tabla 1).

Finalmente se observan diferencias en el rendimiento molar de conversión a SO 4 2-para las distintas disoluciones de tiocianato. Para la concentración de 200 ppm, este rendimiento molar de conversión a sulfatos es cercano al valor teórico (ca. 1), lo que indica que el sulfato es el intermedio de azufre mayoritario. Para menores concentraciones de tiocianato se obtienen rendimientos molares de conversión a sulfato entre 0.5-0.9, lo que sugiere la presencia de otras especies de azufre tales como sulfuros o polisulfuros.

Aguas residuales mineras

Como se ha mencionado anteriormente, se estudiaron cuatro tipos de aguas residuales con distintas concentraciones de cianuro en solución, procedentes de diferentes áreas de la instalación minera. El análisis de los metales comunes de estas aguas residuales, en partes por millón, arrojó los siguientes valores medios: Zn: 0,10; Cd: 0,04; Co: 0,20; Na: 600; K: 26; Ca: 65;

Ni: 0,00; Cu: 80. Otros de los elementos, como Sn, Cr o Pb, se detectaron en concentraciones inferiores a 5 µg/l. Asimismo, la conductividad se encuentra en valores medios de 1050 µS/cm, los sólidos en suspensión en 49 mg/l y la demanda química de oxígeno en 333mg/l.

Inicialmente se comprobó la eficacia del permanganato para la eliminación de cianuro en aguas procedentes del Tanque CIL con una concentración inicial de cianuros de 312 ppm y de tiocianatos de 314 ppm. La figura 3 presenta la tasa de eliminación en función de la relación másica de permanganato potásico empleada. Como se puede observar, se ha logrado alcanzar valores cercanos al 100% para una relación másica KMnO4:CN de 3:1. Posteriormente se estudiaron aguas procedentes del Agua de Proceso de la planta de tratamiento previamente tratada mediante SO 2 , y cuya concentración residual de cianuros se sitúa en las 15 ppm. Los resultados obtenidos se muestran en la Figura 4, con rendimientos de degradación similares a partir de relaciones másicas KMnO4:CN superiores a 4, si bien la degradación no es completa en las condiciones experimentales utilizadas.

Finalmente se realizaron ensayos para el agua de drenaje de la balsa de contención, con una concentración residual de cianuro de 1.9 ppm. En la Figura 5 se observa que a pesar de la baja concentración inicial de cianuros, se alcanzan valores de eliminación cercanos al 70%. Este comportamiento se debe a la oxidación parcial de los tiocianatos de manera simultánea durante la oxidación, los cuales liberan cianuro en la disolución tal y como se ha observado en el análisis de las disoluciones sintéticas (Tabla 2). También es necesario señalar el consumo de permanganato por la materia orgánica en el agua (balsa de desechos en contacto con bacterias y el medio ambiente) [START_REF] Soto | Regeneration of cyanide by ozone oxidation of thiocyanate in cyanidation tailings[END_REF].

De hecho, la tendencia observada es: agua CIL > agua de Proceso > agua de drenaje. Es decir, el rendimiento de oxidación de cianuros aumenta a medida que disminuye la concentración de cianuro en las aguas reales. Esto es debido a la liberación de cianuros como consecuencia de la degradación simultanea de tiocianatos. Éste es un proceso menos favorecido, y por tanto empieza a ser competitivo (y visible en el agua residual tratada) cuando la concentración de cianuros en el agua de partida es suficientemente baja (e.g., agua de drenaje).

Finalmente, se analizó en continuo el agua de proceso durante varias horas recogiendo muestras cada 30 minutos para su posterior tratamiento con una relación másica KMnO 4 :CN de 5 :1, pH= 12 y 20 minutos de agitación (Figura 6). Las diferentes alícuotas tomadas del agua de proceso presentaron concentraciones de cianuros variables entre 33-50 ppm. En todos los casos, se logran eliminaciones importantes de cianuro, cercanas al 95 %, si bien no se logra la degradación completa. Nuevamente, este comportamiento se debe a la degradación simultánea e incompleta de tiocianatos por reacción con el permanganato, dando lugar a la liberación de cianuros en disolución.

CONCLUSIONES

El estudio realizado ha demostrado las propiedades oxidativas del permanganato de potasio para el tratamiento de aguas residuales conteniendo cianuros y tiocianatos procedentes del sector de la minería aurífera. Se ha demostrado la capacidad del permanganato potásico para transformar ambas especies cianuradas en compuestos menos tóxicos, como cianatos, nitratos, amonio y nitritos, a partir de aguas sintéticas e industrial. Se ha evaluado la tasa de eliminación para diversas relaciones másicas permanganato:especie cianurada entre 1-7. En el caso de la oxidación de cianuros, la reacción es cuantitativa en presencia de exceso de permanganato, alcanzándose tasas de degradación cercanas al 100 % y detectándose nitratos como intermedio mayoritario en disolución.

Los ensayos realizados con aguas residuales de mina muestran resultados diversos en función de la concentración inicial de cianuros de las aguas tratadas. Así, se obtienen mayores tasas de degradación de cianuros para las aguas residuales con mayor concentración inicial, con valores de conversión cercanos al 100 % que disminuyen a mediad que lo hace la concentración de cianuro. La determinación de intermedios y el análisis de la oxidación de cianuros y tiocianato en disoluciones sintéticas han confirmado que este comportamiento se debe a la degradación parcial y simultánea del tiocianato presente en las aguas residuales, que liberan cianuros.

La oxidación de tiocianato con permanganato potásico es posible, si bien los datos indican que es una reacción menos favorecida (con una tasa neta de degradación muy inferior a la de cianuro), y que por tanto compite con la degradación de cianuro únicamente cuando éste se encuentra en bajas concentraciones. Los datos sugieren que la degradación completa de las especies cianuradas presentes en estas aguas con elevado contenido en tiocianato implicaría un consumo de reactivo oxidante muy elevado (e.g., relaciones másicas permanganato:especie cianurada superiores a 10), por lo que se precisaría su empleo en tándem con otros proceso para alcanzar la depuración total de las aguas residuales.

AGRADECIMIENTOS

Agradecemos al Gobierno español con sus programas MINECO (grant CTM2014-56770-R) y MINECO (MAT2016-78155-C2-1-R).

BIBLIOGRAFÍA

Ballester A, Verdeja L.F., Sancho J, (2003) Figura 4: Tasa de eliminación de cianuro de agua de proceso pretratada con SO2 (concentración inicial de cianuro de 15 ppm) en función de la relación másica KMnO 4 /CN.

Figura 5: Tasa de eliminación de cianuro de agua de drenaje (concentración inicial de cianuro de 1.9 ppm) en función de la relación másica KMnO 4 /CN.

Figura 6: (A) Tasa de eliminación de cianuro en agua de proceso en continuo para una relación másica KMnO4/CN de 5:1; pH= 12 y 20 minutos de agitación.

(B) Tasa de eliminación de cianuro y tiocianato en agua de proceso en continuo (concentración inicial de 35 ppm de cianuro y 400 ppm de tiocianato).

  sintéticas. La metodología utilizada se recoge en la norma UNE-EN ISO 14403-1:2012 (Calidad del agua. Determinación del cianuro total y del cianuro libre por análisis en flujo (FIA y CFA). Parte 1: Método por análisis de inyección en flujo (FIA)) y consiste en la detección colorimétrica a 610 nm del compuesto generado por reacción con cloramina T, ácido isonicotínico, y acido 1,3 dietilbarbitúrico[START_REF] Nagashima | Spectrophotometric Determination of Cyanide with Isonicotinic Acid and Barbituric Acid[END_REF]. El tiocianato no interfiere en esta determinación.Finalmente, para la medida de tiocianato y de los intermedios de oxidación se utilizó un cromatógrafo iónico de alta resolución modelo 850 Professional IC (Metrohm), provisto de detectores de conductividad y sendas columnas específicas para determinación de aniones (column Metrosep A Supp 7-250, 4 mm × 250 mm, 5 µm), y cationes (Metrosep C3 250/4.0, 4 mm × 250 mm, 5 µm) siguiendo las pautas establecidas en la normaUNE-EN ISO 10304- 1:2009 (UNE 2009). Las columnas se mantuvieron a una temperatura constante de 40 °C. Los eluyentes hicieron circular con un flujo constante de 0,5 mL/min de 3.5 mM HNO3 para la detección de cationes y 3.6 mM Na2CO3 para la detección de aniones. El volumen de inyección para todas las muestras fue de 20 μL. Todas las muestras fueron filtradas a través de un filtro de nylon de 0,45 μm antes de su análisis.

Figura 1 :

 1 Figura 1: Tasa de eliminación de cianuro e intermedios de oxidación a partir de

Figura 2 :

 2 Figura 2: Tasa de eliminación de tiocianato e intermedios de oxidación a partir

Figura 3 :

 3 Figura 3: Tasa de eliminación de cianuro de agua residual CIL (concentración

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	Fundamentos (Madrid: Síntesis).
	Boltz M.M., Terry TI. (2002) Mineral Processing Plant. Design, Practice, and
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	Boltz M.M., MudderT.I. Akcil A.U. (2016) Cyanide Treatment: Physical,
	Chemical, and Biological Processes Gold Ore Processing, pp. 619-645.

TABLAS

  Tabla 1. Tasa de eliminación de cianuro y concentración de especies intermedias detectadas para disoluciones sintéticas de cianuro concentración variable y una relación másica KMnO 4 /CN de 5:1; pH= 12 y 20 minutos de agitación.

	KCN inicial,	KCN inicial,	CN degradado	NO2 -,	NO3 -,	Relacion Molar
	ppm	mM	[%]	mM	mM	Intermedios/CN
	500	19.2	77	9.2	5.4	0.99
	400	15.4	86	8.5	4.3	0.96
	200	7.7	91	3.8	3.1	0.98
	100	3.9	99	2.4	1.4	0.99

Tabla 2. Tasa de eliminación de tiocianato y concentración de especies intermedias detectadas para disoluciones sintéticas de tiocianato concentración variable y una relación másica KMnO 4 /SCN de 3:1; pH= 12 y 20 minutos de agitación.

200 ppm 100 ppm 50 ppm KSCN inicial, mM

			3.45	1.72	0.86
	SCN degradado [%]	19	15	14
	CN -, mM	0.07	0.1	0.03
	OCN -, mM	0.12	0.09	0.02
	NO2 -, mM	0.20	0.03	0.03
	NO3 -, mM	0.14	0	0
	SO4	2-, mM	0.63	0.15	0.23
	NO3 -, mM	0.03	0	0
	Relacion Molar SO4 2-/SCN	0.96	0.58	0.89
	Relacion Molar N-intermedios -/SCN	0.85	0.85	0.68

Vella P, (1996) Sixth International Symposium Chemical Oxidation (Nashville, TN: Technomic, Vanderbilt University), pp. 28-30. Vicente J, Diaz M (2003) Thiocyanate Wet Oxidation; Environmental Science & Technology, 37, pp 1452-1456 Yarar B, (2002) Tailings and Mine Waste: Proceedings of the 9th International Conference, ed. A.A. Balkema (Lisse: Swets & Zeitlinger Publishers), p. 201.