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This paper analyses the potential environmental impacts and economic viability of producing biodiesel from microalgae grown in ponds. A comparative Life Cycle Assessment (LCA) study of a notional production system designed for Australian conditions was conducted to compare biodiesel production from algae (with three different scenarios for carbon dioxide supplementation and two different production rates) with canola and ULS (ultra-low sulfur) diesel. Comparisons of GHG (greenhouse gas) emissions (g CO(2)-e/tkm) and costs (¢/tkm) are given. Algae GHG emissions (-27.6 to 18.2) compare very favourably with canola (35.9) and ULS diesel (81.2). Costs are not so favourable, with algae ranging from 2.2 to 4.8, compared with canola (4.2) and ULS diesel (3.8). This highlights the need for a high production rate to make algal biodiesel economically attractive., (Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.)

Current strategies for monitoring the physiologic status of terrestrial vegetation rely on remote sensing reflectance data, which provide estimates of vigor based primarily on chlorophyll content. Chlorophyll fluorescence (ChlF) measurements offer a non-destructive alternative and a more direct approach for diagnosis of vegetation stress before a significant reduction in chlorophyll content has occurred. Thus, technology based on ChlF may allow more accurate carbon sequestration estimates and earlier stress detection than is possible when using reflectance data alone. However, the observed apparent vegetation reflectance (Ra) in reality includes contributions from both the reflected and fluoresced radiation. The aim of this study is to determine the relative contributions of reflectance and ChlF fractions to Ra in the red to near-infrared region (650-800 nm) of the spectrum. The practical objectives of the study are to: 1) evaluate the relationship between ChlF and reflectance at the foliar level for corn, soybean and maple; and 2) for corn, determine if the relationship established for healthy vegetation changes under nitrogen (N) deficiency. To obtain generally applicable results, experimental measurements were conducted on unrelated crop and tree species (corn, soybean and maple) under controlled conditions and a gradient of inorganic N fertilization levels. Optical reflectance spectra and actively induced ChlF emissions were collected on the same foliar samples, in conjunction with measurements of photosynthetic function, pigment levels, and carbon (C) and N content. The spectral trends were examined for similarities. On average, 10-20% of Ra at 685 nm was actually due to ChlF. The spectral trends in steady state and maximum fluorescence varied significantly, with steady state fluorescence (especially red, 685 nm) showing higher ability for species and treatment separation. The relative contribution of ChlF to Ra varied significantly among species, with maple emitting much higher fluorescence amounts, as compared to corn and soybean. Steady state fluorescence from individual red and far-red emission bands (F685 and F740, respectively) and their ratio consistently enabled species separation. For corn, the relative ChlF fraction increased in concert with the nutrient stress levels from <2% for non-stressed foliage to >7% for severely N deficient plants. Steady state ChlF at 685 nm provided optimal N treatment separation. This study confirms the trends in the steady state red/far-red ratio (F685s/F740s) associated with N deficiency and vegetation stress, previously established using active single narrow band excitation.

Active fluorescence (F) sensing systems have long been suggested as a means to identify species composition and determine physiological status of plants. Passive F systems for large-scale remote assessment of vegetation will undoubtedly rely on solar-induced F (SIF), and this information could potentially be obtained from the Fraunhofer line depth (FLD) principle. However, understanding the relationships between the information and knowledge gained from active and passive systems remains to be addressed. Here we present an approach in which actively induced F spectral data are used to simulate and project the magnitude of SIF that can be expected from near-ground observations within selected solar Fraunhofer line regions. Comparisons among vegetative species and nitrogen (N) supply treatments were made with three F approaches: the passive FLD principle applied to telluric oxygen (O2) bands from field-acquired canopy reflectance spectra, simulated SIF from actively induced laboratory emission spectra of leaves at a series of solar Fraunhofer lines ranging from 422 to 758 nm, and examination of two dual-F excitation algorithms developed from laboratory data. From these analyses we infer that SIF from whole-plant canopies can be simulated by use of laboratory data from active systems on individual leaves and that SIF has application for the large-scale assessment of vegetation.