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MCA - Exploring Algal Carbon Capture Potential in High pH Laboratory- and Field-Scale Systems

$259,850FY2022GEONSF

Citadel Military College Of South Carolina, Charleston SC

Investigators

Abstract

Creative strategies are needed to manage atmospheric carbon dioxide (CO2) to mitigate the consequences of climate change. This research examines, through experiment and modeling, the potential of high pH algal cultures to maximize the amount of inorganic carbon (through dissolved carbon species derived from atmospheric CO2) available for conversion of CO2 to algal biomass. This biomass can then be used for other purposes, such as bio-diesel fuel. To date, high pH algal growth systems have not been adequately explored even though, at these conditions, carbon dioxide is chemically consumed at the air-water inference. To better understand the potential of the high pH/algal system, experiments and mathematical modeling of the data will be used to explore high pH/algal carbon capture processes, feasibility, and performance. The model can be used by researchers and practitioners to estimate the carbon offsets of large-scale cultures aimed at production of high-value produces (e.g., biofuels). Through model development, the research will clarify the role of carbonate and describe how total dissolved inorganic carbon species kinetically interact during algal growth. The impacts of nitrogen-source cycling as a natural, cost-effective strategy to manage pH and improve carbon capture will also be explored. Broader impacts of the work include benefits to society by supporting climate change management and workforce development through designing algal production systems that maximize atmospheric carbon dioxide removal. This can serve as part of an integrated carbon management plan to minimize a myriad of economic, ecological and social consequences of rising temperatures due to high concentrations of greenhouse gases. To carry out the work, students from underrepresented groups in the sciences will be actively recruited. This research entails experiments with mixed algal cultures and the primary product will be an expanded, validated, algal growth model for predicting algal biomass production and carbon capture as a function of interconnected parameters of total dissolved inorganic carbon aqueous species availability, nitrogen source type, and culture pH. High pH is being investigated because at high pH most dissolved total inorganic carbon is converted to dissolved carbonate, whose suitability as an inorganic carbon source has received little attention. Thus, this research seeks to expand and validate a mathematical model to quantify mixed freshwater algal growth in high pH systems to inform future carbon capture experiments. The experiments will be conducted at the Clemson University's Partitioned Aquaculture System. Project goals are to characterize and model total dissolved inorganic carbon-limited growth in batch reactors through the lens of four objectives, the first being to identify and quantify the accuracy of analytical methods for measuring inorganic carbon species at high pH. The second and third are to determine to what extent carbonate kinetically impacts algal growth and determine an appropriate formulation of the Monod-total dissolved inorganic carbon-limited growth rate of mixed culture algae. The fourth goal will be to quantitatively measure carbon capture by the algal cultures in open batch reactors, data that will be used to support model validation. An additional objective will be to explore how nitrogen source cycling could be used to manage pH for carbon capture in the culturing reactor so impacts of nitrogen on pH and biomass production can be estimated and to deliver estimates of carbon capture based on several nutrient loading scenarios. During the project, a graduate student and several additional students will be engaged. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

View original record on NSF Award Search →