Proposal of a Laboratory-Scale Anaerobic Biodigester for Introducing the Monitoring and Sensing Techniques, as a Potential Learning Tool in the Fields of Carbon Foot-Print Reduction and Climate Change Mitigation

: This article presents a proposal of an anaerobic biodigester on a laboratory scale for introducing the monitoring and sensing techniques of the growth of microorganisms according to different parameters, where the redox potential, pH, pressure, and temperature have been measured in quasi-continuous mode. For this task, a microcontroller system was used (Atmega328—Arduino). Importantly, the design is based on ﬂexible and open-source software, hardware, and ﬁrmware (Scilab, Arduino, Processing), facilitating its modiﬁcation for other related studies. This design was developed to help engineering students to learn and to understand the operation of an anaerobic biodigester, which allows us to know various properties of the system at any time, as well as its evolution over time. In this way, property curves can be drawn and related to each other to obtain a better understanding of the biodigester operation. In this context, the relationship between the oxide-reduction reaction and microbial activity was studied so that the redox potential can be a way of measuring the growth of microorganisms in an anaerobic environment. With all this, through these parameters, it is possible to introduce to engineering students the operation of this technology used normally like a very powerful tool for the control of the carbon footprint, for example in wastewater sector, and consequently for the mitigation of the climate change. C.M.-P. and J.V.-R.; visualization, S.B.-E., F.L. and A.R.-M.; supervision, F.L., C.M.-P., J.V.-R. and A.R.-M.; project administration, S.B.-E., F.L. and A.R.-M.; funding acquisition, J.V.-R., F.L. and A.R.-M.


Introduction
Anaerobic digestion technologies, applied to organic water treatment, are efficient ways to solve environmental problems also provide energy. They are considered sustainable, safe, and efficient biotechnologies in which carbon footprint reduction, by CH 4 capture and fossil fuel replacement, is clearly a factor to take under advisement [1][2][3][4][5][6][7]. The process of anaerobic digestion has been known and applied since ancient times; however, it was understood in terms of its final products and not its processes [3]. The versatility of anaerobic digestion applied as an effective technology in the face of certain fundamental challenges has found its usefulness in biotechnological industries [4][5][6][7]. Unlike aerobic processes where dissolved oxygen can be measured continuously, there is a great challenge for fermentative processes in anaerobic organisms where the technologies referring to control processes are currently insufficient [6][7][8][9][10]. Since pH detection has been commonly used in fermentation processes, where only the activity of the proton is reflected, it is not sensitive to small changes in the intracellular metabolism. The redox potential (ORP) known as

Diagram of the Laboratory Reactor
The designed bioreactor ( Figure 1) can be grouped into three distinct parts: (1) Digestion system-which includes the digester itself, as well as those elements that are in direct contact with it (sensors, heating cable, loading, and unloading supply, etc.); (2) Control system, circuits, and voltage source-it receives data and sends the orders necessary for the proper functioning of the system; and (3) Computer system, communication interface and software [40][41][42][43][44]. It is made up of an insulated hermetic container, with a feeding and evacuation system arranged so that the mixture is guaranteed in each loading and unloading process. The upper part of the container has a series of sensors that are defined below:

. Digestion System
It is made up of an insulated hermetic container, with a feeding and evacuation system arranged so that the mixture is guaranteed in each loading and unloading process. The upper part of the container has a series of sensors that are defined below: • pH Sensor: Scientific Grade Silver/Silver Chloride pH), 10 sensor with a response speed of 95% in one second. • ORP sensor, (E): High quality sensor from Atlas Scientific [10,[45][46][47][48]. The data transmission mode is through an integrated system and with a simple serial communication protocol which gives us an immediate response of the E value. • Absolute Pressure Sensor: Phidgets mod. 1141-0-Absolute Sensor of gas pressure from 15 to 115 kPa [49,50]. This is a high-level sensor with analogue input, with input proportional to the of the environment. The pressure measurement for this sensor is 15 kPa. The formula used to translate the sensor value into pressure was the following [2,51,52]: • Temperature sensor: Two miniature Vishay NTC thermistors ( Figure 2) were used to take external and internal temperature readings. Their main characteristics are described in Table 1. For the calculation of the temperature from the analogical measurement, considering the resistive values depending on the temperature provided by the manufacturer, and with an algorithm in Scilab, we obtain Equation (2). Arduino Uno (Figure 3) microcontroller model ATmega328 (Atmel) was implemented within an embedded system in order to control the measuring processes providing bidirectional communication with the circuit of the electrical conductivity probe, transferring the respective data to the PC via USB for archival purposes.

Circuits and Control System
Arduino Uno (Figure 3) microcontroller model ATmega328 (Atmel) was implemented within an embedded system in order to control the measuring processes providing bidirectional communication with the circuit of the electrical conductivity probe, transferring the respective data to the PC via USB for archival purposes. Figures 4 and 5 show the general circuit diagram and pictures where all the elements necessary for the correct operation of the system are collected, as well as the data collection to be processed later. It is composed of a voltage source of 12 V that feeds: the transistor, a heat source, thermistors and a stirring system, a microcontroller hard plate, a PWM plate through which the bioreactor temperature is controlled by a transistor, a plate for the temperature sensors, auxiliary connection plates and sensor plates, resistors, diodes, and wiring. Figures 4 and 5 show the general circuit diagram and pictures where all the elements necessary for the correct operation of the system are collected, as well as the data collection to be processed later. It is composed of a voltage source of 12 V that feeds: the transistor, a heat source, thermistors and a stirring system, a microcontroller hard plate, a PWM plate through which the bioreactor temperature is controlled by a transistor, a plate for the temperature sensors, auxiliary connection plates and sensor plates, resistors, diodes, and wiring.

Circuits and Control System
Arduino Uno (Figure 3) microcontroller model ATmega328 (Atmel) was implemented within an embedded system in order to control the measuring processes providing bidirectional communication with the circuit of the electrical conductivity probe, transferring the respective data to the PC via USB for archival purposes. Figures 4 and 5 show the general circuit diagram and pictures where all the elements necessary for the correct operation of the system are collected, as well as the data collection to be processed later. It is composed of a voltage source of 12 V that feeds: the transistor, a heat source, thermistors and a stirring system, a microcontroller hard plate, a PWM plate through which the bioreactor temperature is controlled by a transistor, a plate for the temperature sensors, auxiliary connection plates and sensor plates, resistors, diodes, and wiring.

Computer System, Communication Interface, and Software
As for the computer system, a data transmission source code was developed for the pH, E, pressure, and temperature sensors with Processing software (source code in Appendix C). The output data was transferred to the Arduino ide serial monitor for checking and control, and then through the Processing software interface for saving into file the sensor samplings.

Auxiliary Equipment and Laboratory Material
The auxiliary equipment were the following: an Atago RX-7000 Alfa3 refractometer used for the effluent measurements, the refraction product, and the Brix degrees ( • Bx); and precision weights. As far as materials are concerned, all those related to the sampling and measurement of volumes (typical of a laboratory) were used, such as flasks, pipettes, spoons, etc.

Computer System, Communication Interface, and Software
As for the computer system, a data transmission source code was developed for the pH, E, pressure, and temperature sensors with Processing software (source code in Appendix C). The output data was transferred to the Arduino ide serial monitor for checking and control, and then through the Processing software interface for saving into file the sensor samplings.

Preparation of the Substrate
For the preparation of the substrate, the procedure described in bibliography was followed [4]. (1) The substrate was prepared, and its suitability checked. (2) The Brix level was measured and verified to be between 17 and 20 degrees. (3) Once this process was finished, 200 mL of the must was taken, and the yeast was added to it (approximately 2-4 g/L). Although an activation temperature of 37 • C is normally required, it was left at room temperature, as it has been previously proven that the inoculum is active under these conditions for working yeast.

Microbial Inoculum
Brewer's yeast was used whose species includes Saccharomyces cerevisiae with a yield of 0.25-0.33 kg of dry cell weight per kg of substrate.

Control and Saving Data
Through the Arduino (Appendix B shows the Arduino source code), the temperature was controlled and the signals from the pH, ORP, absolute pressure, and temperature sensors (inside the digester and outside the environment) were read. Data were sent to the computer where they were stored by means of the use of Processing tool. Shown in Appendix C is the Processing source code, and Figure 6 displays the interface. Once all the information was entered, it was saved in a file on the computer's hard disk. 4 g/L). Although an activation temperature of 37 °C is normally required, it w room temperature, as it has been previously proven that the inoculum is act these conditions for working yeast.

Microbial Inoculum
Brewer's yeast was used whose species includes Saccharomyces cerevisi yield of 0.25-0.33 kg of dry cell weight per kg of substrate.

Control and Saving Data
Through the Arduino (Appendix B shows the Arduino source code), the tem was controlled and the signals from the pH, ORP, absolute pressure, and tem sensors (inside the digester and outside the environment) were read. Data we the computer where they were stored by means of the use of Processing tool. Appendix C is the Processing source code, and Figure 6 displays the interface the information was entered, it was saved in a file on the computer's hard disk.

Digestion Model
Dynamic simulation between reality and model is a very important way for as it enables to provide strategies for the digester operation. In the model, the d of all metabolic rates is based on the classical Monod equation, Figure 6. Processing PC interface data logger.

Digestion Model
Dynamic simulation between reality and model is a very important way for research, as it enables to provide strategies for the digester operation. In the model, the description of all metabolic rates is based on the classical Monod equation, where µ is the growth rate of a considered biomass, µ max is the maximum growth rate of this microorganism, S is the concentration of the limiting substrate S for growth, K s is the half-velocity constant for the substrate S when µ µ max = 0.5. The matrix differential equation related to biomass and substrate dynamic is as follows: where S and X are the substrate and biomass concentration respectively, β s is the stoichiometric ratio for S. Figure 7 shows a simulation with discontinuous dynamics (Scilab source code in Appendix A) with period T = 24 h. Both the evolution of the substrate and that of the biomass, as can be seen in the system, start from an initial state and, after the transitory process, reach a stationary state. lows: where S and X are the substrate and biomass concentration respectively,  is the stoichiometric ratio for S. Figure 7 shows a simulation with discontinuous dynamics (Scilab source code in Appendix A) with period T = 24 h. Both the evolution of the substrate and that of the biomass, as can be seen in the system, start from an initial state and, after the transitory process, reach a stationary state.

Anaerobic Digester Start-Up and Operation
An average representation of the tests, carried out in the biodigester over 5 weeks, is shown in Table 2. The data was processed using a computerised tool from Scilab. Scilab is a software for numerical analysis, with a high-level programming language for scientific calculation. With the obtained data, a series of graphs were elaborated and the most relevant ones are presented in Figures 8-10.

Anaerobic Digester Start-Up and Operation
An average representation of the tests, carried out in the biodigester over 5 weeks, is shown in Table 2. The data was processed using a computerised tool from Scilab. Scilab is a software for numerical analysis, with a high-level programming language for scientific calculation. With the obtained data, a series of graphs were elaborated and the most relevant ones are presented in Figures 8-10. The expression of the oxidation-reduction reactions can be expressed by the Nernst Equation (3).
Product of activities of oxidized species Product of reduced species activities where E 0 is the standard ORP, n is the number of exchanged electrons, and F is the Faraday constant (96.42 kJ/g equivalent volts). The three periods from Table 2 are represented in the graphs as they are the most illustrative. It had taken a time of 1-3000 min for each of them.

First Stage
This stage includes from the start-up of the bioreactor to the first charge/discharge process. Figure 8 shows the ORP, pH, and temperature versus the time, in minutes. The pH profile remains stable with adequate value for fermentative processes, around 4.4, with slight oscillations, while the ORP values indicate, practically, reducing conditions, in a slightly wider range that the previous one. This last achieves its maximum value, 100 (mV), at 1000 min, and minimum value, −250 mV at 1300 min; however, it tends to stabilize with fermentation time. This performance is reflected as well in other works [53,54]. On the other hand, during the whole of this period, temperature moved between 23.6 and 24.6 • C. It is observable that for high value of temperature, the ORP 's graph tends to drop. constant (96.42 kJ/g equivalent volts).
The three periods from Table 2 are represented in the graphs as they are the most illustrative. It had taken a time of 1-3000 min for each of them.

First Stage
This stage includes from the start-up of the bioreactor to the first charge/discharge process. Figure 8 shows the ORP, pH, and temperature versus the time, in minutes. The pH profile remains stable with adequate value for fermentative processes, around 4.4, with slight oscillations, while the ORP values indicate, practically, reducing conditions, in a slightly wider range that the previous one. This last achieves its maximum value, 100 (mV), at 1000 min, and minimum value, −250 mV at 1300 min; however, it tends to stabilize with fermentation time. This performance is reflected as well in other works [53,54]. On the other hand, during the whole of this period, temperature moved between 23.6 and 24.6 °C. It is observable that for high value of temperature, the ORP 's graph tends to drop. In general, the ORP graph shows a downward slope with a very irregular profile.

Second Stage
In this occasion, the system was fed back by 75 mL of a new mixing (see Table 2). From Figure 9, it is observed, in the first third of the stage, a sharp fall in ORP, −85 mV; it In general, the ORP graph shows a downward slope with a very irregular profile.

Second Stage
In this occasion, the system was fed back by 75 mL of a new mixing (see Table 2). From Figure 9, it is observed, in the first third of the stage, a sharp fall in ORP, −85 mV; it immediately increases until it reaches a maximum value, 40 mV, then it begins to decrease gradually. This may have occurred due to the supply of substrate indicating an increase in activity in the first third of the period recorded. The difference in feedstock could change the microbial community and dominant species in anaerobic digestion process. In relation to temperature, the ORP maintains the same vein as that in the previous case.

Third Stage
For this stage, the alkalinity in the reactor was increased by the adding NaOH mixed with the substrate in the follow feeding. The basic environment of the system reflects negative ORP values, between −300 and −470 mV. The graph, Figure 10, shows a gradual decreasing trend of ORP along this period. It is due to the buffering capacity of anaerobic digestion. Similar results have been achieved by other authors [55][56][57][58].

Third Stage
For this stage, the alkalinity in the reactor was increased by the adding NaOH mixed with the substrate in the follow feeding. The basic environment of the system reflects negative ORP values, between −300 and −470 mV. The graph, Figure 10, shows a gradual decreasing trend of ORP along this period. It is due to the buffering capacity of anaerobic digestion. Similar results have been achieved by other authors [55][56][57][58].

Conclusions
The proposed anaerobic biodigester monitored system works well, allowing for small-scale testing. Its use in research and teaching will allow the development of new research projects in the same way that it will help engineering students in their learning. With this design, it will be easy to determine the factors that can affect the growth of the anaerobic microorganism through the continuous data collection by the ORP, pH, tem-

Conclusions
The proposed anaerobic biodigester monitored system works well, allowing for smallscale testing. Its use in research and teaching will allow the development of new research projects in the same way that it will help engineering students in their learning. With this design, it will be easy to determine the factors that can affect the growth of the anaerobic microorganism through the continuous data collection by the ORP, pH, temperature, and pressure sensors. Subsequently, with the subsequent processing of the data, it is possible to make graphs to be contrasted with a previously proposed theoretical model, and at the same time it can be compared with the equations that govern its behavior (Nernst equation).
On the other hand, this design has been supported by flexible and easily accessible free software, this being an important advantage for students since it offers the possibility of adapting this experimental design to each specific case, and the whole software used is free and open source.
The results show that the experimental design is feasible for the control and data collection of magnitudes related to the growth of an anaerobic bacteria in a digester.
Finally, it should be remembered that the design and construction of a laboratory-scale biodigester, due to its economic viability, is a tool available to engineering students for the development of their knowledge and learning.

Data Availability Statement:
In this section, please provide details regarding where data supporting reported results can be found, including links to publicly archived datasets analyzed or generated during the study.

Conflicts of Interest:
The authors declare no conflict of interest.