NMC Team Publishes on Microalgae Productivity in Algal Research
New Mexico Consortium (NMC) scientists, Alina Corcoran, Ahlem Jebali, and Heather Martinez are co-authors on a new manuscript led by UCSD Postdoc Isidora Echenique Subiabre in the journal Algal Research.
This work, titled Site-specific factors override local climatic conditions in determining microalgae productivity in open raceway ponds, is a joint effort between scientists from the NMC, the University of California San Deigo, Colorado State University, Cyanotech, The Energy and Resources Institute, New Mexico State University and Los Alamos National Laboratory.
As demand for sustainable bioenergy and bioproduct feedstocks increases, microalgal cultivation is expanding across the globe.
It is important to understand the forces driving biomass productivities across a range of environmental conditions. Environmental variation significantly affects the response of microalgal growth and thus the location where one should operate commercial scale production of algal feedstocks.
There currently are regionally-resolved predictive models of biomass productivity that use climatic factors such as temperature and light to estimate algal growth to identify the best locations for production sites. Unfortunately, these predictions have rarely been validated at continental scales due to the lack of continuous robust datasets originating from multiple locations simultaneously.
In this study, the scientists established and maintained cultures of Nannochloropsis sp. in open raceway ponds in 150 to 260 L for >17 months at three locations: Kailua-Kona, HI; Las Cruces, NM; and San Diego, CA.
The scientists compared predicted biomass productivities, based on local weather conditions, with experimental field data.
The results of this study found substantial deviations between predicted and observed productivities across and within sites. Although weather remains a pertinent driver of productivity, site-specific factors, such as local pest pressures, chemical/biological contaminants, and differences in the surrounding environment heavily influence biomass productivities.
To create more accurate models to assess potential algal productivity and identify favorable locations for establishing algal production facilities it is important to identify and quantify these local factors.