Due to growing concerns about global climate change and finite fossil fuel resources, governments have been developing policies to reduce fossil fuel consumption and to encourage the development of new, sustainable transportation fuels. The United States Environmental Protection Agency has developed the Renewable Fuel Standard (RFS), which requires that 36 of the annual 140 billion gallons of U.S. transportation fuel mix come from renewable fuel sources by 2022. Innovative and transformational technologies will be necessary to meet these and future renewable energy standards1.
The use of microalgae-based biofuels has the potential to help meet the national RFS while reducing greenhouse gas emissions2. Microalgae-based biofuels have several advantages compared to first-generation biofuels based on terrestrial food crops, such as corn and soybeans. Unlike first-generation biofuels, algae-based biofuels consume fewer land, water, and food-related resources, since algae can be cultivated year-round and on barren land using saltwater or wastewater. Microalgae have high growth rates compared terrestrial crops and can accumulate high levels of lipids, which can be readily converted to biodiesel3. Currently, no industrial-scale algae-to-biofuel plants exist due to the high costs of the energy-intensive production processes, which consist of algal cultivation, lipid separation, and lipid refining into biodiesel. More research is needed to make these processes more efficient and sustainable.
PBRs, which are optically clear, enclosed installations for the production of phototrophic microorganisms in an artificial environment, are considered one of the most promising cultivation methods3. However, current designs still lack the volumetric productivity necessary to make the algae-to-biofuel production process more efficient and economically attractive4. Powerful mathematical models that consider light irradiance and attenuation, the transport of nutrients and CO2, and the growth of the microalgae can greatly facilitate the optimization of PBR design and operation. Bench-scale growth experiments are required to determine species-specific growth parameters for these optimization models.
Kinetic tests require the careful monitoring and control of experimental setups to prevent unintended inhibitors of growth. Given the photosynthetic nature of algae (i.e., their consumption of CO2 and absorption of light), maintaining controlled conditions is especially difficult in bench-scale PBRs. As depicted in Equation 1, the amount of dissolved CO2 in the growth medium, commonly denoted as
(Equation 2), will be, at minimum, a function of: 1) the CO2 partial pressure and Henry's equilibrium constant, which dictates the amount of gas that will dissolve in solution (Equation 3); 2) the initial chemical composition of the growth medium, which impacts the speciation and activity of the carbonate ions and pH (Equations 4 and 5); and 3) the temperature, which impacts Equations 3-55.



![figure-introduction-5 Static equilibrium equation Ka1(T) = [H+][HCO3-]/[H2CO3], chemical balance analysis diagram.](/files/ftp_upload/55545/55545eq5.jpg)
![figure-introduction-6 Equilibrium constant equation \(K_{a2}\) for bicarbonate-carbonate equilibrium, formula \(K_{a2} = \frac{{[H^+][CO_3^{2-}]}}{{[HCO_3^-]}}\).](/files/ftp_upload/55545/55545eq6.jpg)
The various phases and the chemical speciation of carbon create a challenge for measuring and maintaining a consistent dissolved carbon concentration within a PBR while holding other conditions constant (e.g., the pH increases as the algae consume CO2, and increasing the dissolved CO2 substrate can possibly lead to an acidic environment that inhibits growth)6.
An additional layer of complexity for controlling conditions during algal kinetic tests involves the light intensity within the PBR. The average light intensity inside a PBR is a function of not only the incident light intensity, but also the design (e.g., material, shape, depth, and mixing), the absorbance of algal biomass components (particularly chlorophyll), and the light-scattering properties of the algal cells. As the algae grow, the average light intensity will decrease. This change in light intensity, whether caused by an increase in total cells and biomass, an increase in chlorophyll content per cell, or both, can eventually induce a metabolic response, such as an increase in chlorophyll production per cell or the use of carbohydrate and lipid storage products for energy7. Continuous monitoring of the light intensity from within the reactor provides invaluable information. This data can help to ensure that conditions stay within a specified range and can be used to help estimate algal growth and absorbance parameters if combined with other measurements (i.e., biomass, chlorophyll concentration, reactor depth, incident light, etc.).
Understanding how algae grow under a specified set of conditions requires that the pH, dissolved CO2, light intensity, and temperature be monitored in bench-scale kinetic experiments. Many algal growth setups are not equipped to monitor conditions to the extent required for calibrating kinetic models, making the modeling process extremely challenging8. Although many companies offer bench-scale PBRs with automation and control, these bench-scale setups can be extremely expensive (~$20,000) and might not accommodate all experimental considerations of a given research question.
The first step in setting up a control-feedback system for a batch experiment is live data acquisition. This paper aims to demonstrate how to construct and set up a bench-scale PBR equipped with continuous light, pH, and temperature monitoring. This real-time monitoring setup can help to ensure that the experimental conditions stay within desired ranges, at the researcher's discretion. While this protocol does not detail specific control mechanisms, these step-by-step instructions provide a basic foundation for the data acquisition framework required before more sophisticated control feedbacks can be implemented.