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Title: Incorporation of salinity, nitrogen, and shading stress factors into the Huesemann Algae Biomass Growth model

Abstract

This research calibrates nitrogen, salinity and shading growth factors for The Huesemann Algae Biomass Growth (HABG) model. It continues the HABG approach of independently calibrating growth coefficients for specific strains prior to simulation of algal growth in open pond raceways. Several Regional Algal Feedstock Testbed (RAFT) had salinity stress, nitrogen limitation, and shading, which all reduced growth rate. The salinity effect appeared to be most significant in Scenedesmus obliquus experiments. In order to quantify these effects, la- boratory experiments were carried out to measure growth response of S. obliquus to high salinity and limited nitrogen. In addition, the shading effect was estimated based on raceway geometry, solar angle, albedo, and measured light intensity data. The new salinity, shading, and nitrogen stress factors greatly improved the accuracy of the model with the observed growth conditions. Over-estimation was decreased from 90% to 22%. The methods developed in this study are straightforward and can be applied to other algae strains and raceways.

Authors:
; ; ; ORCiD logo; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1492710
Report Number(s):
PNNL-SA-140554
Journal ID: ISSN 2211-9264
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Algal Research
Additional Journal Information:
Journal Volume: 35; Journal Issue: C; Journal ID: ISSN 2211-9264
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
Huesemann algae biomass growth model, ARID raceway, Salinity, Nitrogen, Shading

Citation Formats

Gao, Song, Waller, Peter, Khawam, George, Attalah, Said, Huesemann, Michael, and Ogden, Kimberly. Incorporation of salinity, nitrogen, and shading stress factors into the Huesemann Algae Biomass Growth model. United States: N. p., 2018. Web. doi:10.1016/j.algal.2018.09.021.
Gao, Song, Waller, Peter, Khawam, George, Attalah, Said, Huesemann, Michael, & Ogden, Kimberly. Incorporation of salinity, nitrogen, and shading stress factors into the Huesemann Algae Biomass Growth model. United States. doi:10.1016/j.algal.2018.09.021.
Gao, Song, Waller, Peter, Khawam, George, Attalah, Said, Huesemann, Michael, and Ogden, Kimberly. Thu . "Incorporation of salinity, nitrogen, and shading stress factors into the Huesemann Algae Biomass Growth model". United States. doi:10.1016/j.algal.2018.09.021.
@article{osti_1492710,
title = {Incorporation of salinity, nitrogen, and shading stress factors into the Huesemann Algae Biomass Growth model},
author = {Gao, Song and Waller, Peter and Khawam, George and Attalah, Said and Huesemann, Michael and Ogden, Kimberly},
abstractNote = {This research calibrates nitrogen, salinity and shading growth factors for The Huesemann Algae Biomass Growth (HABG) model. It continues the HABG approach of independently calibrating growth coefficients for specific strains prior to simulation of algal growth in open pond raceways. Several Regional Algal Feedstock Testbed (RAFT) had salinity stress, nitrogen limitation, and shading, which all reduced growth rate. The salinity effect appeared to be most significant in Scenedesmus obliquus experiments. In order to quantify these effects, la- boratory experiments were carried out to measure growth response of S. obliquus to high salinity and limited nitrogen. In addition, the shading effect was estimated based on raceway geometry, solar angle, albedo, and measured light intensity data. The new salinity, shading, and nitrogen stress factors greatly improved the accuracy of the model with the observed growth conditions. Over-estimation was decreased from 90% to 22%. The methods developed in this study are straightforward and can be applied to other algae strains and raceways.},
doi = {10.1016/j.algal.2018.09.021},
journal = {Algal Research},
issn = {2211-9264},
number = C,
volume = 35,
place = {United States},
year = {2018},
month = {11}
}