Abstract
The unprecedented decline in petroleum reserves along with the rising concerns of global warming and environmental pollution has resulted in the search for alternative energy. India receives an abundant amount of solar insolation that can be easily transformed into other bioenergy sources. In current years, microalgal biofuels have gained attention owing to the presence of substantial amount of lipids and ease of cultivation in the presence of light energy, wastewater, and carbon dioxide (CO2). In spite of the theoretical knowledge, the lack of convincing technical data and economic hindrances limit their field-scale application. The current study utilizes the global horizontal solar irradiance data (from the year 2002 to 2008) of India as input into the photon energy balance equations, which were solved in MATLAB to predict the theoretical microalgal biomass, lipid productivity, and CO2 sequestration potential. The maximum biomass productivity was predicted as 90.1 g m−2 d−1, corresponding to the lipid productivity of 31.3 ml m−2 d−1 and CO2 sequestration potential of 23.6 g m−2 d−1 in the southern peninsular regions and Western Ghats. Since the solar irradiance varies from 3.25 to 6.08 kWh m−2 d−1 for the entire Indian subcontinent, most parts of India were projected to be suitable for growing microalgae. Decline in biomass productivity by 32.5% was evident accounting for photoinhibition effects such preliminary estimates would help in assessing the real-time potential of microalgae before going for cost-intensive field-scale analysis.
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Acknowledgements
The authors are thankful to the Department of Biotechnology and Medical Engineering, NIT Rourkela, for providing the necessary facilities to carry out this research work. The authors greatly acknowledge the Ministry of Human Resources Development, Government of India, for sponsoring the Ph.D. program of the first author.
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Behera, B., Aly, N., Asok Rajkumar, M., Balasubramanian, P. (2019). Theoretical Estimation of the Microalgal Potential for Biofuel Production and Carbon Dioxide Sequestration in India. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 816. Springer, Singapore. https://doi.org/10.1007/978-981-13-1592-3_62
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