Microalgae have been of interest as a feedstock for biofuels but until recently have not been economically feasible. Recent energy uncertainties coupled with technological advancements have made microalgae more appealing as an alternative feedstock for transportation fuel. Algae characteristically have many advantages over traditional terrestrial based biofuel feedstocks. Prior to commercialization of the microalgae to biofuels process there are technological challenges that need to be overcome.
The work presented can be divided into three primary modeling efforts, a process level analysis, bulk growth evaluation, and a diffuse versus direct light evaluation. All models presented are experimentally validated and used to assess the near term realizable impact of microalgae. Results from this work are intended to accurately represent the current state of the field by more accurately representing the current potential and technologies being explored.
Biofuels derived from microalgae have the potential to replace petroleum fuel and first-generation biofuel, but the efficacy with which sustainability goals can be achieved is dependent on the lifecycle impacts of the microalgae-to-biofuel process. This work proposes a detailed, industrial-scale engineering model of the growth, dewater, extraction, conversion, and transportation and distribution stages of the microalgae to biofuels process for the species Nannochloropsis using a photobioreactor architecture. This process level model is integrated with a lifecycle energy and greenhouse gas emissions analysis compatible with the methods and boundaries of the Argonne National Laboratory GREET model, thereby ensuring comparability to preexisting fuel-cycle assessments. Results are used to evaluate the net energy ratio (NER) and net greenhouse gas emissions (GHGs) of microalgae biodiesel in comparison to petroleum diesel and soybean-based biodiesel with a boundary equivalent to “well-to-pump”. The resulting NER of the microalgae biodiesel process is 0.93 MJ of energy consumed per MJ of energy produced. In terms of net GHGs, microalgae-based biofuels avoids 75 g of CO2-equivalent emissions per MJ of energy produced. The scalability of the consumables and products of the proposed microalgae-to-biofuels processes are assessed in the context of 150 billion liters (40 billion gallons) of annual production.
A more detailed bulk growth model has been assembled to more accurately represent the growth of microalgae. To date, there is little published data on the productivity of microalgae in growth systems that are scalable to commercially viable footprints. To inform the development of more detailed assessments of industrial-scale microalgae biofuel processes, this paper presents the construction and validation of a model of microalgae biomass and lipid accumulation in an outdoor, industrial-scale photobioreactor. The model incorporates a time-resolved simulation of microalgae growth and lipid accumulation based on solar irradiation, species specific characteristics, and photobioreactor geometry. The model is validated with 9 weeks of growth data from an industrially-scaled outdoor photobioreactor. A sensitivity of the model input parameters is presented.
The model presented was used to more accurately represent the current US productivity potential. Current calculations for the large-scale productivity potential of microalgae are based on growth data from small-scale non-industrially representative systems. To accurately assess the near-term large-scale microalgae potential, a thermal basin model is presented and combined with a bulk growth model previously validated with industrial-scale outdoor photobioreactor growth data. The combined models require meteorological data to accurately predict microalgae growth and lipid production. This study integrates 15 years of hourly historical weather data from 864 locations in the US to accurately assess the current productivity potential of microalgae in the US. Geospatial information system (GIS) land availability and slope data are used to generate a set of dynamic maps of the current feasible locations and productivity potential of microalgae in the US based on a variety of geographic characteristics and restrictions. A comparison of model results based on optimal location with current productivity potentials reported in literature shows the need for more realistic estimation of microalgae growth potential for future LCA.
The bulk growth model does not differentiate between diffuse and direct light growth. The microalgae growth as a function of diffuse versus direct light with the application to reactor design evaluation was evaluated for Nannochloropsis salina experimentally with modeling applications. For the application to large scale cultivation modeling and evaluation, a small scale reactor representative test apparatus was constructed to investigate the growth response of Nannochloropsis salina under a variety of real world relevant light intensities and temperatures on a batch growth time scale with the intention of modeling growth in larger scale devices. Growth data was also collected from two geometrically different large scale indoor photobioreactors under a variety of light intensities for model evaluation. The application of small scale data to accurately predict growth at large scale enables the evaluation of photobioreactor geometry. Temperature experimentation illustrates the detrimental effect that temperatures above 30 °C and below 7 °C have on microalgae batch growth. Discussion focuses on the application of the data set to reactor design and evaluation and modeling efforts and evaluation of photic volume data reduction. Results show a significant difference in growth from direct light compared to diffuse light and the difficulty of photic volume growth modeling.
The work presented uses the results of a high level environmental assessment of microalgae biofuels to guide further research in growth modeling and process evaluation based on pilot plant experience. A more detailed bulk growth model incorporating 21 species and reactor specific characteristics with primary inputs of light and temperature was developed from literature and validated with real world large-scale photobioreactor data. This model was used to illustrate the current microalgae productivity potential in the US. This modeling effort illustrated the need for a more fundamental understanding of diffuse versus direct light utilization in microalgae cultivation. Experimental setup was designed and operated to generate a photosynthesis irradiance curve. This curve was used to inform a model validated with growth data from large scale photobioreactors. This data was directly used in the evaluation of photobioreactor geometry and used to investigate optimum geometry based on the metric of areal productivity.
The experimentally validated models presented are used to critically evaluate the current state of the microalgae to biofuels process. Previous efforts have made unrealistic assumptions leading to the mis-representation of the environmental impact and productivity potential of microalgae.