Mechanical and Aerospace Engineering and.
Department of Wildland Resources, Utah State University, Logan, UT 84322.
Proc Natl Acad Sci U S A. 2014 Jun 10;111(23):8691-6. doi: 10.1073/pnas.1321652111. Epub 2014 May 27.
In the current literature, the life cycle, technoeconomic, and resource assessments of microalgae-based biofuel production systems have relied on growth models extrapolated from laboratory-scale data, leading to a large uncertainty in results. This type of simplistic growth modeling overestimates productivity potential and fails to incorporate biological effects, geographical location, or cultivation architecture. This study uses a large-scale, validated, outdoor photobioreactor microalgae growth model based on 21 reactor- and species-specific inputs to model the growth of Nannochloropsis. This model accurately accounts for biological effects such as nutrient uptake, respiration, and temperature and uses hourly historical meteorological data to determine the current global productivity potential. Global maps of the current near-term microalgae lipid and biomass productivity were generated based on the results of annual simulations at 4,388 global locations. Maximum annual average lipid yields between 24 and 27 m(3)·ha(-1)·y(-1), corresponding to biomass yields of 13 to 15 g·m(-2)·d(-1), are possible in Australia, Brazil, Colombia, Egypt, Ethiopia, India, Kenya, and Saudi Arabia. The microalgae lipid productivity results of this study were integrated with geography-specific fuel consumption and land availability data to perform a scalability assessment. Results highlight the promising potential of microalgae-based biofuels compared with traditional terrestrial feedstocks. When water, nutrients, and CO2 are not limiting, many regions can potentially meet significant fractions of their transportation fuel requirements through microalgae production, without land resource restriction. Discussion focuses on sensitivity of monthly variability in lipid production compared with annual average yields, effects of temperature on productivity, and a comparison of results with previous published modeling assumptions.
在当前的文献中，基于微藻的生物燃料生产系统的生命周期、技术经济和资源评估依赖于从实验室规模数据推断出的生长模型，这导致结果存在很大的不确定性。这种简单的生长建模方法高估了生产力潜力，并且未能纳入生物效应、地理位置或培养结构。本研究使用基于 21 个反应器和物种特异性输入的大型、经过验证的户外光生物反应器微藻生长模型来模拟 Nannochloropsis 的生长。该模型准确地考虑了营养物质吸收、呼吸和温度等生物效应，并使用每小时的历史气象数据来确定当前的全球生产力潜力。根据在全球 4388 个地点进行的年度模拟结果，生成了当前短期微藻脂质和生物量生产力的全球地图。在澳大利亚、巴西、哥伦比亚、埃及、埃塞俄比亚、印度、肯尼亚和沙特阿拉伯等地，最大的年平均脂质产量在 24 到 27 m³·ha-1·y-1 之间，对应的生物量产量为 13 到 15 g·m-2·d-1。本研究的微藻脂质生产力结果与特定地理区域的燃料消耗和土地可用性数据相结合，进行了可扩展性评估。结果突出表明，与传统的陆地饲料相比，微藻生物燃料具有很大的潜力。在不限制水、营养物质和 CO2 的情况下，许多地区通过微藻生产有可能满足其运输燃料需求的很大一部分，而不会受到土地资源的限制。讨论集中在脂质生产的月变异性与年平均值相比的敏感性、温度对生产力的影响以及与以前发表的建模假设的比较。
