different approaches to life cycle assessment (LCA ...

Review

Evaluating microalgae-to-energy systems: different approaches to life cycle assessment (LCA) studies Massimo Collotta, Leonardo Busi, University of Brescia, Italy Pascale Champagne, Warren Mabee, Queens University, Kingston, Ontario, Canada Giuseppe Tomasoni, Marco Alberti, University of Brescia, Italy Received June 3, 2016; revised August 5, 2016; accepted August 8, 2016 View online at Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/bbb.1713; Biofuels, Bioprod. Bioref. (2016) Abstract: Life cycle assessment (LCA) is a valuable tool for determining the environmental impacts associated with different products and has been widely used to assess biofuel production. As a scientific methodology rather than a standardized test, every LCA may be thought of as unique in terms of the selection of functional units or determination of system boundaries. Researchers generally tailor the method to meet the specific goals of their own investigations. This review examines a number of LCAs used to evaluate microalgae-to-energy systems, and evaluates their contributions in terms of their ability to support commercialization efforts in this sector. To this end, a new scoring system for LCAs is proposed based on input/output flows, data origin, production technologies and system boundaries, selection of assumptions and variables, as well as the ability to track environmental, economic, and social impacts. The review suggests that, while a wide variety of new technological pathways for microalgae-to-energy systems are being assessed, the majority of studies reported employ relatively limited system boundaries that may not capture the full impacts of the processes. The number of environmental impact factors being tracked is limited, and many studies do not consider important impacts such as water or land use. Most studies do not incorporate critical information about economics related to new process configurations, which will be essential to support commercialization efforts in this area. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd Keywords: life cycle assessment (LCA); microalgae; biodiesel; review; guidelines; biofuel

Introduction

B

iomass for energy, and particularly liquid biofuels for use in transport, have been of increasing interest to policymakers seeking to shift toward more sustainable economies. The development of green fuel technologies with minimal carbon emissions is one

option that can help meet global energy requirements in a more sustainable fashion, reducing society’s over-reliance on fossil fuels, which currently meet 80% of the world’s energy demand.1 There is great potential for the use of microalgae as a sustainable feedstock for biofuels, and particularly for biodiesel production, as these micro-organisms are highly

Correspondence to: Pascale Champagne, Department of Civil Engineering, Queens University, Ellis Hall, 58 University Avenue, K7L 3N6 Kingston, Ontario, Canada. E-mail: [email protected]

© 2016 Society of Chemical Industry and John Wiley & Sons, Ltd

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efficient producers of lipids.2,3 Lipid content in microalgae is highly dependent on species and cultivation conditions; and some authors have claimed to have achieved lipid contents as high as 70% on an algal biomass dry weight basis.4 Multiple technological pathways have been proposed for the commercial production and harvest of microalgae, and microalgae feedstocks are being surveyed for a variety of different products. Protein-rich feed for livestock, food supplements for humans, electricity production from anaerobic digestion (AD), fatty acid feedstocks for biofuels, and biochar are among the products currently being investigated.5,6 While commercial production of microalgae-based biodiesel has yet to be proven environmentally sound or economically feasible, researchers note that ideal microalgae strains or consortia for biodiesel production should be characterized by year-round cultivation, the ability to use waste water as a nutrient source, higher solar energy yields, and minimal use of arable land.7–9 Microalgae can be cultivated in both salt water and fresh water environments, and it has been suggested that they are suited to areas where the cultivation of crops could be, marginal, challenging, or expensive. Applying life cycle assessment (LCA) to evaluate the environmental performance of microalgae for biodiesel production is an ongoing endeavor, and a number of scientific studies on this biofuel pathway have already been published outlining a variety of approaches and methods.5,10,11 Some authors have attempted to draw some general conclusions, emphasizing the uncertainty of results, due to the early developmental stage of the technology and the assumptions made concerning the electricity mixture,12 and highlighting the need for a standardized approach to LCA studies in this field.13,14 In the absence of major demonstration projects, however, there remain many unanswered questions regarding real energy consumption, greenhouse gas (GHG) emissions, and other environmental impacts. At this point, it is difficult to contrast existing studies regarding the production of microalgae-based biofuels, due to differences in the supply chain and/or production technologies being considered. This review attempts to answer an important question: are the LCAs currently being reported providing the appropriate type of information necessary to support a sound assessment of the commercialization of efficient microalgaeto-energy pathways? To address this question, a number of recently published LCA analyses describing various microalgae-based production processes are reviewed. The studies are ranked based on their use of primary data and presentation of sensitivity analyses, as well as the range of impact categories assessed. The discussion then considers

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Review: Biodiesel from microalgae: a LCA studies review

the system boundaries employed in these studies, ranging from the production to distribution, and the environmental impact factors that are reported in the analysis. Finally, the potential to introduce economic or social factors into the analyses are considered and the impact categories proposed to measure these factors are noted.

Review of existing studies Selection and overview of studies This study initially identified and examined 23 analyses of microalgae-to-energy systems. Of these studies, 18 were found to have utilized an LCA approach and were selected for further investigation to better understand the ramifications of utilizing different sources of data, process configurations, and system boundaries. Pertinent data, including the year of the study, primary energy output, LCA tools utilized, and jurisdiction where the study was carried out have been tracked. The inclusion of primary data and/or sensitivity analyses in the LCA were also noted. The list of selected studies (arranged in alphabetical order) is shown in Table 1. A cursory overview of the studies available suggests that most LCAs describing microalgae-to-energy conducted between 2009 and 2015 suffer from a lack of primary data, which is largely related to the commercial-scale microalgae-to-energy technologies and facilities. Because of the general lack of existing large-scale processing facilities, the majority of studies have utilized secondary data, which provide a higher level of uncertainty, to describe hypothetical (but hopefully practical) system designs.12,13 By comparison, the majority of the LCAs carried out in this space utilize sensitivity analyses to test the impact of changing variables and conditions. This is a positive thing, since sensitivity analyses allow the evaluation of the impact of uncertainty in the LCA models. The vast majority of the studies in this space consider biodiesel as an end product, but also include a range of other products such as biojet fuel, methane, and bio-oil. Seven of the 18 LCAs evaluated systems in North America (6 in the USA), followed by 3 each in Asia and Australia, and 6 in the EU. A wide range of tools were used in these studies, including commercial soft ware (e.g. SimaPro), specialized models (e.g. GREET), and open-source tools (e.g. OpenLCA). The metadata shown in Table 1 highlight the range in geographies, products, and tools used in assessing microalgae-to-energy systems. This diversity could affect a range of factors, including input variables, and thus change the overall projected impacts of these systems. One set of factors that can dramatically change the anticipated impact

© 2016 Society of Chemical Industry and John Wiley & Sons, Ltd | Biofuels, Bioprod. Bioref. (2016); DOI: 10.1002/bbb

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Table 1. Overview of 18 LCAs describing microalgae-to-energy pathways. LCA #

Reference

Year of Functional Unit study

LCA tools employed GREET 1.8a and Crystal Ball

LCA database

n/s

Country

Included Presented primary sensitivity data analysis

1

Baliga and Powers20

2009

Production of 1 l of Biodiesel

USA

2

Batan et al.7

2010

Production of 1 MJ of Biodiesel

GREET 1.8c

n/s

USA

3

Brentner et al.24

2011

Production of 10 GJ of Algal methylester

Simapro

Ecoinvent 2.2

USA

P

4

Campbell et al.6

2010

Transport of 1 t km

Simapro 7.0

ESAAE, AusLCI, Ecoinvent

Australia

P

5

Clarens et al.21

2009

Production of 317 GJ Biomass

Excel and Crystal Ball

Ecoinvent

USA

P

6

Clarens et al.18

2011

1 Vehicle Kilometer travelled

Excel and Crystal Ball

Ecoinvent

USA

7

Collet et al.15

2010

Production of 1 MJ Methane & Electricity

n/s

Ecoinvent

EU

8

Cox et al.25

2013

Production of 100 MJ Biojet

Simapro 7.3.3

Ecoinvent

Australia

P

9

Gnansounou et al.29

2015

Production of 1 kg Biodiesel

Simapro 7.3.3

Ecoinvent

India

P

10

Khoo et al.40

2010

Production of 1 MJ of Biodiesel

n/s

n/s

Singapore

P

11

Lardon et al.17

2009

Combustion of 1 MJ of fuel

n/s

Ecoinvent

12

Malik et al.32

2014

Production 1 Mt of Biocrude

MRIO

MRIO

13

Slade and Bauen36

2012

NER of biomass production

Gabi 4

n/s

14

Stephenson et al.22

2010

Combustion of 1 t of biodiesel

openLCA 1.4

Ecoinvent 2.2

USA

15

Tsang et al.31

2014

1 h of operation of the marine vessel

n/s

n/s

China

P

16

Yang et al.23

2010

Production of 1 kg of biodiesel

Gabi 5

Ecoinvent 2.2

Mexico

P

17

Holma et al. 2013

2013

Production 1 MJ of biofuel

n/s

Different sources

EU

18

Collet et al. 2014

2014

Combustion of 1 MJ of algal methylester

n/s

Ecoinvent

EU

P

P

n/s Australia

P

UK P

P

P P

n/s – included but not specified.

of microalgae-to-energy systems is the choice of process technologies, and the delineation of system boundaries utilized in the LCA. The next section defi nes the process stages involved in microalgae-to-energy systems, and assesses the selected LCAs based on the inclusion of these various stages within system boundaries.

Process stages for biodiesel production The production of biodiesel from microalgae consists of a number of different, discrete, and sequential production stages. Most of the 18 papers included in this analysis consider a production system which goes from cultivation, through harvesting, dewatering, and lipid extraction to transesterification. A selection of the studies includes three additional stages – biomass recovery and use, biofuel transport (from production facilities to users), and biofuel use. This aspect is particularly relevant, since system boundaries

that likely exclude important factors may limit the scope of the assessment.14 The whole set of the microalgae-to-energy production system phases is shown in Fig. 1. Each process phase identified in Fig. 1 can employ different technologies/chemicals/processes. For the cultivation phase, the production systems analyzed by the selected studies include one of two pathways which have each been explored extensively for the production of microalgae. Photobioreactors (PBRs) are enclosed chambers for microalgae growth subjected to natural or (in northern climates) artificial light; these systems often present higher productivities compared to open raceway ponds (ORPs) – shallow oval ponds exposed to air and light – which are likely to have lower operating costs, despite having higher net energy ratios and lower productivity rates.15,16 Different pathways for the harvesting and dewatering phases are also utilized in the selected studies, each with advantages and disadvantages. The most commonly


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Figure 1. Generalized microalgae-to-biofuel production process.

considered processes are flocculation (stimulating the formation of solids – flocs – within the microalgal slurry) and centrifugation. The two processes can be combined, where a biomass concentration of 20% by weight can be achieved by flocculation (using organic, inorganic flocculants, or other novel flocculants) followed by centrifugation of the flocs.17 The energy required for stirring and pumping the culture medium and flocculants employed to achieve biomass precipitation are factors that influence the environmental impacts of this phase. Energy use may be decreased through process innovation; for example, increasing PO4 concentration in the growth medium can lead to a phenomenon called auto-flocculation in which the microalgae aggregate in flocs and then precipitate from the culture medium. Auto-flocculation does not require as much energy and may, hence, exhibit lower overall environmental impacts.18 Other approaches, not in the selected studies, explored the harvesting phase adopting the high pressure CO2 without any addition of coagulants in order to separate algae from suspension.19 Drying is an important stage as it is a high consumer of energy; this stage is required to increase the percentage of dry matter from about 20% up to 90–95%; the precise target percentage depends on the lipid extraction process requirements. The selected studies considered belt dryers, solar and steam dryers, natural gas dryers and co-combustion with coal.17,20–23 In one case, the potential environmental benefits coming from the use of waste heat from another industrial process (an electricity generation plant) has been explored.20 Different approaches are also used by the selected studies for the lipid extraction phase. The aim of this production step was the separation of lipids from the remainder of

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the biomass. In all the cases considered, the extraction is assisted with the use of solvents (hexane, methanol, and ethanol), in some case with additional steps such as a drill pressing24 or dry de-gumming.25 None of the studies take into consideration more advanced approaches currently under exploration, such as the innovative use of switchable hydrophilicity solvents (SHS) at room temperature that use CO2 for separation and no required a drying of the solvent prior to use, 26 or the CO2 expanded methanol approach (adopted from Paudel et al.27) which presents better lipid extraction yields. In the transesterification phase, lipids and alcohols are transformed into methyl or ethyl esters and glycerol. In the studies analyzed, this reaction is driven with esterification, sonication with a direct esterification and Honeywell UOPTM process.24,25 In one case, the direct transesterification has been adopted, which using supercritical conditions combines the lipid extraction and transesterification in a single phase with wet biomass. In this case, a reaction between triglycerides and methanol takes place at a temperature and pressure over the critical point of this mixture. This is an energy-intensive process, but avoids the use of large amounts of heat energy in the drying of biomass.24 The transportation phase is the last step before biofuel usage and was generally done using trucks or pipelines, depending on the volumes produced or location of the plant. It is often suggested that facilities for the production of biofuels should be placed wherever is most convenient, whether close to the feedstock supply, or close to end users.7,22 In some cases, facilities could be placed conveniently close to the sources of inputs, for example close to a cement plant (as a source of CO2) or a waste-water treat-


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ment plant (as a source of water and nutrients).20,28 The use of waste water throughout the process seems to be promising way to improve the environmental and economic sustainability of algae cultivation.33–35 Finally, the end use of the energy product is considered. Baseline comparisons between bio-based product (e.g. biodiesel, biojet) and their petroleum-based counterparts suggest that the impact of some substitutions – for instance, replacing coal-fired electricity – may lead to more significant environmental offsets than others.35 Understanding the end-use of the microalgae-based energy product was essential to understanding the overall impact of the system. The introduction of biomass recovery and use is important because residual biomass can support other energy generation opportunities. It can be utilized as feedstock for bioethanol production, 29 or subjected to anaerobic digestion (AD) to produce methane,15,22,24,25,30 which can then be used for the production of electricity – either for sale, or for in-house use to reduce the fossil energy demand associated with microalgae processing.22 The waste biomass can also be used for animal feed.25,31 as soil amendments, or it can be landfi lled. Another possible use for waste biomass is hydrothermal liquefaction in which moisture biomass is subjected to a high temperature treatment (250–300 °C) and pressure (10–20 MPa) in order to produce bio-crude oil.32 In some LCA studies, wastewater has been investigated as a potential source of nutrients for microalgae cultivation. Moreover, different types of wastewaters (e.g. centrate) have been used as input flow in the production stage of biodiesel process. Similarly, flue gas from industrial plants (e.g. cement plants) has been evaluated as a potential source of CO2 . 28,35 The co-location of microalgae production facilities with wastewater treatment plants (or anaerobic digestion facilities) can provide access to nutrients, waste energy and CO2 , would could maximize the use of waste resources in the process and increase the techno-economic feasibility of the overall process. 20,28 Recovery of waste heat and flue gas for the generation of energy products could assist industrial partners in reducing carbon costs under cap-and-trade or carbon tax regimes. Using waste streams to drive microalgae growth may lead to a reduction in the cost of cultivation-related activities and a net reduction in GHG emissions. 36,37 Table 2 provides a summary overview of different technologies available for microalgae-to-energy process that have been considered in the selected LCAs, as well as an indication of the stages (from cultivation to end product

phases) that were incorporated in the system boundaries of each LCA. The importance of the defi nition of system boundaries in the methodological approach has been shown in a number of studies.42 For example, comparative LCA studies require an equivalent defi nition of system boundaries for the alternatives being compared, as well as system delimitations coherent with the goal defi nition. This is relevant not only for the environmental impacts, but also for the social and economic considerations. As can be seen from Table 2, only one of the 18 LCAs considered each of the eight process stages; two additional studies consider seven of eight, and two consider six of the process stages. The most commonly ignored process stage was the transportation of energy products from the production facility to the point of end use; only two studies considered this stage. The second most commonly overlooked process stage was end product use; only 9 of 18 LCAs included end-product use within their system boundaries. The results summarized in Table 2 highlight the importance of avoiding direct comparisons between LCA results obtained from different analyses using different system boundaries. Each study selected specific process components for inclusion in their assessment, and were seeking to obtain specific knowledge about the system under investigation. However, the results would also suggest that the lack of consensus among researchers regarding the impacts of microalgae-to-energy systems may stem from the lack of consistency in defining system boundaries.

Measuring impacts Environmental impact factors The environmental impact factors measured in each of the 18 LCAs under review are presented in Table 3. In the majority of the studies, the environmental impact categories considered were aggregated, such as global warming potential (GWP) and abiotic depletion. In other cases, they were specific, distinguishing energy consumption instead of using abiotic depletion as a measure of the fossil fuel used for energy production.21,30 As the production of third generation microalgae-based energy is increasing being cited as a climate change solution,1 it is not unexpected that GWP was the dominant environmental impact factor measured in the majority of the LCAs selected, appearing in 17 of 18 studies. The GWP is representative of the emissions of several greenhouse gasses (primarily CO2, N2O, CH4). Within the microalgae-to-energy production chain, these are generally the


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Table 2. Production stages and processes included in selected LCAs.

P P

4

P

5

P

P

6

P

Pd

7

P

8

P

9

P

10

P

11

P

12

P

13

P

14

P

P

15

P

P

16

P

P

17 P

P

18 P

P

P

P

P

Pe

P

P

P

P

P

P

P

P

P

P Ph

P n/s P

P

P

P

P

P

P

P

n/i Pf

P

P

P

n/i

P

n/i n/i

P

Pg

P

n/i

n/i

n/i

n/i

n/i

n/i

P

P P n/i

P

P

P

P n/i n/i

P

P

P

P n/i

P n/i

Combustion/co-generation

Biojet

P

n/s

P

P

P

n/i

P

P

Pi

n/i P

n/i

P P

Biodiesel

Conveyor

Truck

Other

Landfill

Soil amendments

Other

Supercritical methanol

Methanol + Acid

Honeywell UOPTM

n/i P

n/i

n/i

P

n/i

P

n/i P

n/i P

P n/i

n/i P

Pj

P

P

n/s

P

Pc

P

n/i

P

n/i

n/i

P

Pb Pb Pc P

n/i

P

n/i

P

n/i P

P

P P

Biofuel use

n/i

P

P

P P

P

P

Transportation Residual biomass use

Methanol + ROH

P

Other

n/i P

Supercritical CO2

Pa

Hexane (+methanol/ ethanol)

P

Homoginization

Dissolved air flotation

Mechanical press

Natural/gravity settling

Dryers

2 3

n/i

Filtration

Flocculation

P

Lipid extraction

Centrifugation

1

Photobioreactor (PBR)

Open raceway ponds (ORP)

LCA #

Harvesting

Trans-esterification

Animal feed

Dewatering

Anaerobic digestion, CH4- energy

Cultivation

P

l

P

n/i n/i P n/i

P

P

P

P n/i

n/i

n/i

n/i

P

n/i

P

n/i

P n/i

n/s – included but not specified; n/i – not included Notes: asteam drying; bdrill press+hexane; csonication+esterification; dauto-flocculation; eco-combustion with coal; fde-gumming; gethanol, protein extraction; hbelt dryer; ihydrothermal liquefaction; jsolar/natural gas driers; lglycerin, digestate solids reduction.

products of fossil fuel combustion for the generation of electricity and heat, the use of gasoline or diesel for product transportation, or the manufacturing and use of chemicals required in the process. While GWP is important, other related impact factors were also commonly noted in the LCAs under consideration, including energy use (10 studies), fossil resource depletion (5 studies), and abiotic depletion (consumption of natural but non-renewable resources – 3 studies). GHG emissions associated with microalgae-to-energy systems were primarily related to energy consumption in the harvesting, dewatering/drying, lipid extraction and transesterification phases. Some studies suggested that harvesting and dewatering could contribute up to 20–30% of operational costs38,39 while other studies identified the

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lipid extraction and transesterification phases as having the highest energy demands.40 Energy demand in operational stages could be reduced through the introduction of new processes for recovering and utilizing the microalgal biomass for energy production, such as anaerobic digestion or pyrolysis. It should be noted that electricity and heat availability differ significantly between countries, and that impact factors related to these energy sources could change significantly with a changing energy mix.41 Thus, it is essential that these factors be described using regional data that reflects the most current understanding of the energy mix. For this reason, local electricity mix (the average fuel mix for the electricity generation) had a significant influence on the final results. It is evident that a microalgae-to-


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1

P

2

P

3

P

4

P

5

P

6

P

7

P

8

P

9

P

10

Pb

11

P

12

P

13

P

14

P

P

P

P

P

P

P

P

LCIA methodology

Abiotic depletion

Energy use

Land use

Water use

Marine toxicity

Ecotoxicity

Respiratory effects

Eutrophifcation

Acidification

Ionizing radiation

Photochemical oxidation

Human toxicity

Ozone depletion

Global warming potential

LCA #

Table 3. Environmental impact categories utilized in 16 LCAs.

n/s

P

Pa

n/s

P

CED v1.07, BEES v4.02

P

n/s P

P

P

P P

P

P

P

P

P P

P

n/s

P P

P

n/s

P

P

P

CML

P

Recipe midpoint

GHG inventory

P

P

n/s

P P

P

P

P

P

P

P

P

P

P P

P

P

P

P

P

P

P

EDIP 2003

P

TRACI v2.1

Pc

15

n/s Pd

16

P

17

P

P

18

P

P

P P

P

P

P

P

CML, CED n/s

P

P P

P

n/s P

EU RED

P

Recipe midpoint

Notes: aincludes material use; bCO2 emissions; cincludes nutrient use; dprimary energy.

energy system that utilizes waste heat, or derives electricity from an onsite anaerobic digestion plant, could substantially reduce fossil GHG emissions and likely decrease overall operational costs. Other important considerations when evaluating microalgae production systems are the land and water requirement, and a group of environmental impact factors can provide insight regarding the use of these resources. Water availability, highly dependent on geographic location, is often the most critical factors affecting operational feasibility and cost. While both fresh and salt water can theoretically be used, fresh water represents fewer issues in terms of operational costs, because salt must be extracted from sea water via an evaporation phase and then disposed of.42 In addition, sunlight potential and temperature of the location have been shown to directly influence the growth rate of the algae.1 The need for both heat and a high proportion of sunny days governs the potential land requirements for outdoor algae production.32 If ORP systems were selected, the site required for microalgae production would necessar-

ily require large surface area systems. In regions with high land costs, this kind of technology may become prohibitive unless it can be deployed within existing industrial facilities. On arable lands, the use of land for microalgae production may raise concerns regarding impacts on food supply. Although water and land use are clearly important impact factors to consider when evaluating microalgae-toenergy systems, only 12 of 18 studies included land use (9 studies), water use (8 studies), and eutrophication (7 studies). This might suggest that water and land use were not monitored as regularly as greenhouse gas emissions; this limitation may suggest a paucity of data or a lack of understanding of the importance of these factors.

Economic and social criteria One clear issue that emerges from the previous discussion is that a number of changes in process design will be needed to meet specific economic criteria. An understanding of environmental impacts rarely appears to be


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Table 4. Economic and social impact factors in two LCAs. LCA #

Economic Analysis Impact Category

4

Life cycle costs

12

Economic stimulus of microalgae-to-energy

Measurement

Impact Category

Production cost (including tax incentives)

Employment (algal industries)

$ generated per $ invested

Employment

the primary driver behind new process designs. At the same time, however, most of the studies presented in this review draw from bench-scale operations in the absence of commercial facilities; few of the LCAs report on the potential economic impacts related to the scaling-up of these processes. An assessment of economic impacts related to process operations is essential to anticipate the capital and operating costs associated with a commercial venture. While many speculate that microalgae-to-energy systems are likely to contribute positive benefits in terms of environmental, economic, and social impacts, based on current understanding, microalgae-to-biodiesel systems have been presented to have a low economic feasibility related to the high costs of dewatering and extraction during the process.6 The ability to integrate capital and operating costs would seem to be an important addition to environmental impact assessments. It would also be beneficial to include policy measures, such as renewable fuel mandates, carbon pricing, or excise tax exemptions, that are present in the jurisdiction under consideration. Very few LCA studies had incorporated economic or social impact factors, but two of the 18 LCAs reviewed in this study did incorporate some measures, and one in particular presented an innovative hybrid LCA that integrated economic and social analyses along the supply chain.32 Table 4 presents a summary of economic and social impact factors included in these studies. In terms of economic analysis, life cycle costing (used in one study6) was a useful way of tracking the total cost of production; this impact factor builds on the life cycle approach and, with the inclusion of sufficient information, should give a robust estimate of production costs. In fact, it includes not only plant facility and main operational costs, but also items often neglected by other cost estimation methodologies, such as the costs for research and development, design, failures, contribution margin loss, corrective and preventive maintenance and plant final disposal. For example, cost estimates could estimate the impact of increased or decreased water volume or arable land use.43,44 Similarly, the economic analysis could

8

Social Analysis Measurement Unemployment index Full time equivalent workers required (FTE)

determine the feasibility of using regional waste streams as resources (CO2, waste water, waste heat) and high algal production rates.28 Determining the economic impact of an investment, as was conducted in one study,32 was a more arm’s-length approach of measuring benefit as it required an accurate estimate of economic returns (i.e., gross and net profit) as well as accurate measurements of investment. Having stated this, both measures are useful when determining commercial investment. The latter approach may be informed by LCA, but required significantly more understanding of market conditions. Th is particular study suggests that the microalgae-to-biodiesel industry provides a greater monetary stimulus than traditional crude oil production processes.32 In terms of social measures, the two studies selected employment as the impact category to track. The actual measures differed slightly; where one study24 examined employment but couched their reporting in reference to the unemployment index, while Malik et al. simply tracked the full-time workers required to run the planned system.32 These studies suggested a higher number of employees for microalgae-to-energy systems compared to comparable food and nutraceutical production,10 as well as conventional crude oil production facilities.29 The implication is that the effect that microalgae-to-energy facility may have on host communities, given the labor force demand deriving by this plant, should be considered for a complete analysis. Other factors that may also be useful to measure social impact may include human rights, labor conditions and health and safety benefits, as well as corruption and their effects on the legal system.45 This could be done using the impact categories suggested in the Guidelines for Social-LCA (S-LCA) issued by UNEP/SETAC.46–48

Scoring system The lack of transparency in data sources and the reliability of data have been identified as critical factors in the application of LCA.36 For this review, a scoring system was used to evaluate the accuracy of data collection and processing


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1

1

1

1

0.4

0.3

1

3.7

0.4

0.3

1

3.7

1

Final score (/6)

1

1

Economic, social impact factors

1

Environmental impact factors

4 12

Process steps in system boundary

1

Sensitivity analysis presented

Full LCA methodology employed

14

Primary data used

LCA #

Table 5. Final scoring of 16 LCAs describing microalgae-to-energy pathways.

5

18

1

1

0.6

1

3.6

7

1

1

0.6

1

3.6

17

1

1

0.8

0.7

3.5

8

1

1

0.8

0.7

3.5

3

1

1

0.8

0.3

3.1

9

1

1

0.8

0.3

3.1

16

1

1

0.8

0.3

3.1

5

1

1

0.3

0.7

3

10

1

1

0.6

0.3

2.9

1

1

1

0.5

0.3

2.8

11

1

0.8

1

2.8

15

1

0.4

0.3

2.7

13

1

0.9

0.3

2.2

6

1

0.8

0.3

2.1

2

1

0.6

0.3

1.9

1

provided in each phase. In the proposed scoring system, a total of six points could be awarded. One point was assigned if a complete LCA was performed. Another point was assigned if primary data (i.e., data collected for the purpose of the LCA) was utilized, and an additional point was awarded if a sensitivity analysis was conducted and included in the publication. Up to one point was assigned depending on the number of process stages that were included within the system boundaries of the study (e.g., 6 process stages would be awarded 6/8 or 0.8). Similarly, up to one point was awarded based on the number of environmental impact factors that were assessed in each study: for studies that reported 8 or more impact factors, a full point was awarded; 4 to 7 impact factors, 0.7 points; 1 to 3 impact factors, 0.3 points. Finally, the last point was assigned if economic or social impact factors were included. The scoring results are shown in Table 5. This scoring system could assist in identifying the most robust LCAs currently available in the existing literature. As shown in Table 5, none of the 18 LCAs analyzed in this review was judged to provide the full range of

information required for commercialization efforts related to microalgae-to-energy systems. One study22 scored very high, while four others6,15,25,32 each had highly comparable scores, but for different reasons – two benefited from included economic and social impact factors, for example, and two included primary data in their analyses. While some studies have relatively low final scores, this should not be taken as an indication that these studies were flawed; rather this score reflects a singular focus within the study at hand – for example, interest in GHG emission reductions. By the same token, LCAs with high scores are more likely to include multiple impact factors reflecting a range of environmental concerns, and may include social or economic factors of interest to developers of these technologies. The analysis suggests that only a few of the LCAs are well equipped to inform commercialization efforts; others, while useful, are focused on a narrow range of issues.

Discussion One of the most important ways in which the LCAs under consideration differ is in their selection of system boundaries, which is defi ned by the processes and products under consideration. The review highlights a wide range of process configurations and suggests that few of the LCAs currently published in this space consider the full range of process stages identified; in fact, 12 of 18 LCAs studied 5 or fewer stages, with the most commonly omitted stages including the transportation of biofuel to end users and end product use. While it is recognized that the introduction of innovative technologies in all production phases is essential, the authors suggest that unless all process stages are considered, the studies will be limited in their evaluation of environmental impacts unless the entire microalgae-to-energy system can be assessed. In this review, only one study had provided information on all eight process stages. The review also noted that the many LCAs focused on only a handful of environmental impact factors. Global warming potential (as measured via greenhouse gas emissions) was most commonly investigated, and a range of related impact factors were sporadically considered. Water and land use, highly significant in microalgae production systems, were not nearly as well described in the selected studies. A little more than 50% of the studies included one or more of these factors. This reflects the fact that researchers are focused on the ability of microalgae-to-energy systems to meet global warming challenges. Because water consumption could be significant in microalgae production


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systems, it is essential that these factors be considered when considering commercial applications. It should be noted that the knowledge gap with respect to important sets of impact factors may also reflect a lack of data, primary or other, to describe these systems. This review also showed that, for the most part, published LCAs do not take into account economic and social implications of microalgae-to-energy systems. In fact, only two studies introduced some aspects of the economic and social benefits of biodiesel production. The economics associated with new process configurations is a critical piece of information for the future commercialization of these systems. Similarly, the social impact (e.g. employment) associated with developing this industry may provide an impetus for the development and deployment of these technologies. Life cycle costing, as used by one of the studies reviewed, is one approach for the evaluation of economic impacts that builds directly on the LCA approach, and as such could provide robust data linkable to the system under assessment. Employment, which is the measure most often used to evaluate social impact, is also something that can be linked to process stages and evaluated within the LCA framework. It should be noted that the identification of potential environmental impacts could include impacts on human health, and as such could inform this dimension. Although the integration of the economic and social considerations in the sustainability assessment of microalgae to energy systems still presents a high level of uncertainty, due to their early technological developmental stage, the reference to similar technologies for data gathering and the adoption and consolidation of methodological approaches, such as the social LCA,51–53 may assist in overcoming some of the techno-economic challenges and address some of the uncertainties currently faced by this industry with respect to full-scale implementation.

Conclusion In conclusion, a large number of LCAs have been published examining microalgae-to-energy systems; these studies cover a wide geographical range, and examine a number of interesting process configurations which may lead to biofuels with lower environmental impacts and better cost structures. Our review finds that the majority of these studies do not have access to primary data but utilize secondary data sources. Most studies fail to consider every process stage and thus cannot be used to comment on the overall impacts of microalgae-to-energy production. Only about half of the studies reviewed consider the impacts of water and land use, and only two present

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detailed information on economic and social impacts. While all of these studies represent valuable contributions toward the knowledge base, only a small number of LCAs present data that can be directly used to support commercialization efforts in this area. Acknowledgments The authors gratefully acknowledge funding from the Ontario Ministry of Research Innovation (Ontario Research Fund). Additional funds were provided via a National Science and Engineering Research Council (NSERC) Strategic Project Grant and through the Canada Research Chairs Program. Finally, the authors thank BioFuelNet Canada for funding support and access to data during the writing of this paper.

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Pascale Champagne Prof. Pascale Champagne completed her PhD in Environmental Engineering 2001 from Carleton University. She is a Professor in Civil Engineering with a cross-appointment to Chemical Engineering at Queen’s University. She holds a Canada Research Chair in Bioresource Engineering. She has been recipient of a number of research awards and was inducted into The College of New Scholars, Artists and Scientists in the inaugural cohort of the Royal Society of Canada in 2014. She has published more than 85 journal papers in reputable journals in her field, 9 book chapters and her work has been presented in more than 175 conference presentations.

Massimo Collotta Massimo Collotta completed his PhD in Design and Management of integrated logistic and productive system at University of Brescia in 2015. He’s a Postdoctoral Research Fellow at the Department of Mechanical and Industrial Engineering of Brescia University in collaboration with Queen’s University (Canada). He holds a degree in Industrial Engineering from Brescia University. His main research interests include Life Cycle Assessment (LCA) methodologies, renewable energy, waste management technologies and manufacturing process management.

Leonardo Busi Leonardo Busi received an Undergraduate Degree in Industrial Engineering at University of Brescia in 2015. He is a Master student in Industrial Engineering and Management at University of Brescia and he spent 4 months at Queen’s University (Kingston, Canada) for an Internship on biofuels production during his Master degree. His activity focuses on Life Cycle Assessment studies on biofuel production, in particular on biodiesel production from microalgae.

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Warren Mabee Dr. Warren Mabee (Ph.D. 2001, Toronto) holds a Canada Research Chair (Tier 2) in Renewable Energy Development and Implementation. He is an Associate Professor at Queen’s University, with a joint appointment in the School of Policy Studies and the Department of Geography. His international research programme focuses on the interface between policy and technology in the area of renewable energy and fuels, addressing issues that bridge the gap between researchers and decisionmakers. He has done extensive work on economic and life cycle assessment of renewable energy systems and sustainable bioproducts, and works closely with the forest and agricultural sector as alternative energy options become more integral to these industries. His past work experiences include stints at the University of British Columbia and the University of Toronto, as well as the Food and Agriculture Organization of the United Nations. Dr. Mabee is currently Associate Task Leader (Policy) for the International Energy Agency’s Bioenergy Task 39 and Director of the Queen’s Institute for Energy and Environmental Policy.


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Giuseppe Tomasoni Giuseppe Tomasoni is an Assistant Professor of Industrial Mechanical Systems Engineering at the Mechanical and Industrial Engineering Department of the University of Brescia (Italy). His research field includes environmental management systems, LCA, work safety and industrial ergonomics. He has participated and is currently participating to three research projects funded by the Life program of the European Union (Cosmos, Cosmos-Rice and Life-Med) leading life cycle analyses of new technologies.

Marco Alberti Marco Alberti is Full Professor of Industrial Mechanical Systems Engineering at the Mechanical and Industrial Engineering Department of the University of Brescia (Italy). His research interests include environmental management systems, LCA, safety at work and industrial ergonomics. He is the Coordinator of the PhD Course in design and management of integrated logistic and productive systems at the University of Brescia. He has been member of national and international commissions and work groups of the main standardization bodies (UNI, ISO) in the environmental field, safety and ergonomics. He has participated and is participating to three projects funded by the Life program of the European Union (Cosmos, Cosmos-Rice and Life-Med) leading life cycle analyses of new technologies


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