Sustainability analysis of microalgae production systems - A review on

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Cite This: Environ. Sci. Technol. 2018, 52, 14031−14049

Sustainability Analysis of Microalgae Production Systems: A Review on Resource with Unexploited High-Value Reserves Arun K. Vuppaladadiyam,†,‡,∥ Pepijn Prinsen,§,∥ Abdul Raheem,†,‡,∥ Rafael Luque,§,⊥ and Ming Zhao*,†,‡ †

School of Environment, Tsinghua University, Beijing 100084 China Key Laboratory for Solid Waste Management and Environment Safely, Ministry of Education, Beijing, 100084, China § Departamento de Química Orgánica, Universidad de Córdoba, Campus de Rabanales, Edificio Marie Curie (C-3), Ctra. Nnal. IV, Km 396, Córdoba, Spain Downloaded via EAST CAROLINA UNIV on January 11, 2019 at 12:16:32 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.

‡

S Supporting Information *

ABSTRACT: Sustainability, at present, is a prominent component in the development of production systems that aim to provide the future energy and material resources. Microalgae are a promising feedstock; however, the sustainability of algae-based production systems is still under debate. Commercial market volumes of algae-derived products are still narrow. The extraction and conversion of primary metabolites to biofuels requires cultivation at large scales; cost-effective methods are therefore highly desirable. This work presents a complete and up to date review on sustainability analysis of various microalgae production scenarios, including techno-economic, environmental, and social impacts, both in large-scale plants for bioenergy production and in medium-scale cultivars intended for the production of high added-value chemicals. The results show that further efforts in algal-based research should be directed to improving the productivity, the development of multi product scenarios, a better valorization of coproducts, the integration with current industrial facilities to provide sustainable nutrient resources from waste streams, and the integration of renewable technologies such as wind energy in algae cultivars.

1. INTRODUCTION The global population could reach and even exceed 9 billion by 2050.1 The development of efficient conversion methods that use sustainable feedstocks to meet the growing global energy demand and to reduce the use of fossil resources, is now an imminent challenge for the research community. Around 87% of the global CO2 emitted by anthropogenic activities result from fossil resources, with coal, oil, and natural gas contributing 43, 36, and 20%, respectively.2 In the EU, ca. 30% of the total energy use is spent in transport fuels.3 One way to convert CO2 and light energy into renewable fuels, chemicals and energy is to store them in microalgae (biosequestration). Microalgae can fix CO2 more efficiently than terrestrial plants (with biomass yields ca. 55 kg ha−1 year−1, twice as high) and do not directly compete with food crops for arable land.4,5 Still, significant bottlenecks exist in the road toward sustainable commercial microalgae derived production systems, due to techno-economic, environmental and social constraints and challenges in their cultivation, harvesting and associated downstream processes. Recently, various reviews have been published in the field of sustainable microalgae based production systems, including conversion to biofuels6−9 and high added-value chemicals.10−12 © 2018 American Chemical Society

Some of them focused on specific sustainability aspects such as the use of industrial flue gas as CO2 source13 or wastewater (WW) as nutrient source,14−16 and environmental applications.17,18 Some reviews deal with techno-economic assessment (TEA) studies,19−21 others with life cycle analysis (LCA),22−24 and some with socio-economic indicators.25 Rather few works evaluated the sustainability in all its aspects.26,27 As progress is continuously being developed in various fields, including metabolic engineering, cultivation, harvesting, extraction, and conversion, these review studies may help to clear out favorable routes toward sustainable industrial algal production systems. The data available in the literature is hardly assesed in a quantitative manner because they are rather dificult to compare due to differences in model definitions, assumptions, and boundaries and the high amount of biorefinery scenarios and input parameters used. The present work aims to evaluate the sustainability of different microalgae biorefinery scenarios in a quantitative and Received: Revised: Accepted: Published: 14031

May 29, 2018 November 8, 2018 November 12, 2018 November 12, 2018 DOI: 10.1021/acs.est.8b02876 Environ. Sci. Technol. 2018, 52, 14031−14049

Critical Review

Environmental Science & Technology

Figure 1. Minimum biomass selling price in TEA scenarios 1−7.

up to date study based on techo-economic assessment and lifecycle analysis. Key papers from the last seven years on TEA and LCA studies were selected. Production costs of algal biomass, algal oil/biocrude, and algal biofuel were contrasted by comparing MAFBSP (minimum ash-free biomass selling price) and MFSP (minimum fuel selling price) in various biorefinery scenarios together with high impact variables (according to the sensitivity analysis if any). MAFBSP and MFSP refer to prices to obtain a zero net present value (NPV) for a specified internal rate of return after taxes, typically set at

10% target). MAFBSP and MFSP are accounting concepts, not real selling prices. Higher MAFBSP/MFSP means that the (final) product needs to be sold at higher value for revenues and inflow cash reaching breakeven level of the original capital investments. To correct these cost data for the currency and inflation between different publication years, MAFBSP and MFSP values are expressed in USD (2018), recalculated with the mean annual currency and inflation rates (with respect to publication year). Next, important findings from the literature are highlighted involving sensitivity, cost breakdown and 14032

DOI: 10.1021/acs.est.8b02876 Environ. Sci. Technol. 2018, 52, 14031−14049

Critical Review


biosequestration methods (scenarios 6a−6j).35 The cultivation method (ORP/PBR) and photosynthetic efficiency (PE) were also included as variables. The effects were rather small and the production costs were low in all cases compared with other studies, possibly due to the effect of other variables such as productivity, lipid content, and scale. The substantial lower cost also may have resulted from MAFBSṔs definition; in this case it was calculated at an electricity price similar to that from a conventional PP without CO2 capture and storage. Important parameters in the selection of a suitable cultivar location include not only the estimated PE and seasonal variations, but also governmental regulations and labor costs as illustrated in scenarios 7a−7d. Ruiz et al. (2016) reported a tidous and realistic analysis of ORP and PBR cultivars.27 They compared the capital and operational costs on a 100 ha scale from current production facilities in several countries. They concluded that FPPBR are the most cost-effective production system, with the best projections for southern Spain (3.4 EUR kg−1). 2.2. Algae Harvesting. Algae harvesting (often followed by dewatering) is a bottleneck step, as it contributes considerably in the overall biomass production cost.36,37 The energy consumed during harvesting and dewatering can account up to 90% of the total energy required for algal biodiesel production.38 Typically, algae slurries ca. 1 wt % dry solids must be dewatered to ca. 20 wt %. Centrifugation technologies work efficient but face large initial capital investments. Supporting Information (SI) Figure S1 shows the effect of the cell density and lipid content on the energy use and the cultures size required to produce 1 L of algal oil, showing that centrifugation should be considered more appropriate as a final step in dewatering methods, especially at large scales. Aggregation by flocculation and coagulation is one of the most cost-effective harvesting technologies.39,40 Bioflocculation (BF) occurs at pH > 9, whereas chemical flocculation techniques cover a broader pH range, employing cationic iron, aluminum salts, lime, cellulose, polyacrylamide polymers, cationic starch, or surfactants to alter the physiochemical interaction between algae cell walls (negatively charged) and induce the formation of aggregates. Around 95% cell flocculation efficiency was achieved when the pH of Nannochloropsis sp. cultures (107 cells mL−1) was adjusted to 10 by adding Ca(OH)2.41 The corresponding harvesting cost was estimated as low as 7.5 USD ton−1 biomass and was further reduced to 3.5 USD ton−1 when the cell density reached 108 cells mL−1. When using chitosan flocculation (CHF) in a preconcentration step, Xu et al. found that up to 95% of the energy required for harvesting via centrifugation can be saved.42 Despite the promising results, chemical flocculation is not the best option from an environmental point of view, especially when using aluminum salts.38 Chemical flocculation technologies also face lower biomass recovery, typically 1−20% lower compared to other harvesting methods.43 In some cases, negative effects can be observed in product quality.40 Harvesting microalgae via aqueous ammonia hardly affected the metabolites content distribution. The liquid fraction may be reused as nutrient feed for algae cultivation.44 Aggregation induced by micro-organisms avoids the use of chemical flocculants.45,46 However, relatively large inoculant sizes (30:1) were needed and flocculation was rather slow. Powell and Hill accelerated the BF process drastically and reduced the bacteria cell:algae cell ratio to 1:1.47

market analysis, which are important tools in TEA studies. In the section on LCA, net energy ratios (NER), greenhouse gas (GHG) emissions and water footprints (WF) were compared for the most prominent scenarios. All energy balances were expressed as NER values. Data were also collected on algal biomass productivities using different wastewater (WW) sources to evaluate their potential as nutrient source. In the last section, various indicators of socio-economic impacts are highlighted. Finally, based on the main conclusions, future prospects for algae-based research and commercial production systems are summarized.

2. TECHNO-ECONOMIC ASSESSMENT (TEA) Production systems must be techno-economically viable to be sustainable. This aspect is currently still on debate in algae based biorefinery, due to the large uncertaincy in the extrapolation of lab-scale data to large scale scenarios and depending on the data available for every biorefinery scenario and the model boundary limits, giving raise to a high degree of heterogeneity among the data.26−29 2.1. Algal Biomass Production. An important part in the cost distribution is attributed to the algae biomass production itself. This includes cultivation and harvesting. Figure 1 shows the biomass production cost of various algal production systems including open raceway ponds (ORP) and photobioreactors (PBR). The results show considerable variations in production costs (MAFBSP), depending on the input parameters used and assumptions made in the TEA scenarios. In some cases the production cost is competitive with the U.S. soybean market price as the benchmark feedstock for competitiveness with first generation biodiesel, whereas in other cases it largely exceeds it. The U.S. 2022 target price (entry 3) of 2.25 USD kg−1 may be a better reference for comparison.52 The large differences in production costs are mainly the effect of varying biomass productivity, scale, cultivation method, and nutrient costs. The highest impact variable was the scale of biomass production (1, 10, 100, and 400 ha in scenarios 1−2). But, the scale of economy effect may be subjected to uncertainty, as real life data are rather scarce (instead they are extrapolated from lab-scale or pilot scale data). The economy of scale effect in algae production systems is limited by the modular character of the cultivation systems.27,30 The cultivation method affects the cost considerably, as illustrated for ORP, tubular (TPBR) and flat-plate (FPPBR) photobioreactors in scenario 1. Hoffmann compared algal turf scrubbers (ATS, scenario 4a) with classic ORP cultivars (scenario 4b).33 ATS systems are based on native cultures which dynamically adapt to changing conditions to improve the culture stability and avoid crash events. The lipid content of ATS algal biomass was however low (10%) and they presented high ash content. Nevertheless, the ATS cultivars produced algal biomass at 2620 USD ton−1, whereas ORP cultivars at 3460 USD ton−1, mainly due to the difference in cell density at harvesting (200 vs 0.5 g L−1, respectively). Rotating algal biofilm reactors (RABR, scenarios 5a−5e) are another innovative cultivation method.34 The effect of zero cost nutrients is also noticeable (scenarios 2a and 2c vs 2b and 2d). Some studies reported the use of WW as nutrient feed source and the supply of CO2 from flue gas sources, but not all of them included the carbon credits associated with the estimated storage and pump costs. Rezvani et al. studied the integration of cultivars with different CO2 14033


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Figure 2. MFSP of algal lipid oil/biocrude in TEA scenarios 1−7.

Direct filtration, cross-flow filtration, or combinations with inverse osmosis were also demonstrated to recover algae aggregates efficiently.48−50 NAABB researchers assembled a thin porous nickel-alloy metal-sheet membrane in a cross-flow module for dewatering microalgae cultures up to 24% solids.51

Filter pore sizes need to be carefully designed in function of the aggregation rate, as smaller cells ( 0). Maximizing FAME yields in compromise with lower LEA yields for animal feed lead to a negative NPV. Batan et al. reported the capital and operational costs for a PBR cultivar intended for RD production via WSE followed by HT.60 Surprisingly, the harvesting costs were estimated much higher than those reported by Doshi et al. (ORP),69 despite no use of flocculant was reported and despite exhibiting higher biomass concentrations at harvest. Although higher capital investment was required to purchase PBR, the installation cost and working

capital was considerably lower compared to ORP. Hoffman contrasted the cost analysis of ATS against ORP cultivars intented for RD production via HTL and HT.33 The total capital investment was similar whereas the operational cost was drastically lower for ATS cultivars, as it was assumed that all nutrients were provided from WW streams (without credits for removing N and P) and that CO2 was provided by a nearby source of flue gas. Flocculants were not required for dewatering of ATS cultures (algae can be harvested at concentrations up to 200 g L−1) in contrast with ORP cultures (harvested at 0.5 g L−1). Recently some hybrid PBR-ORP cultivars were analyzed, in which algal strains are inoculated in PBR followed by large scale growth in ORP.70 The hybrid system showed attractive capital investment requirements. Capital costs of 269, 83, and 101 million USD year−1 for PBR, ORP and hybrid PBR-ORP, respectively (0.7−108 dry ton year−1). The effects on the operational costs were similar. 2.6. Sensitivity Analysis. Sensitivity analysis is an important tool in TEA, as it indicates more clearly the fields that must be improved in the road to commercial algae production systems. It shows how a certain output value (MFSP, NPV, t-values, etc.) varies with a changing input parameter in the calculation model (Excel, AspenPlus, FARM, etc.), including a baseline case, a lower case and an upper limit case, in the form of probability curves, histograms, etc. BravoFritz et al. (2016) considered an interesting set of biorefinery scenarios and compared them between Isochrysis sp. and Tetraselmis sp. cultivars at medium and large scale sizes.70 All the scenarios (SI Figure S4) resulted in negative NPV, except for protein extraction (albeit it had the worst energy balance evaluation). The most promising scenarios included (a) drying + ball-milling + lipid/debris separation, (b) WSE, and (c) WSE + anaerobic digestion (AD). The effect on MFSP of the assessment context (moderate, intermediate, and optimiztic) and the scale were actually more significant than the biorefinery scenario itself. Only with Isochrysis sp. in the optimiztic scenario and at large scale competitive production costs (MFSP) were achieved ca. 1 USD L−1. Here is the point where TEA results start to get speculative; data on larger scale are required to confirm the data used from small scale. One successful example of this was reported by Wen et al. (2016)71 on the up-scaling of Chlorophyta cultivars from pilot scale (0.01 m3 reactor) to outdoor (40 m3 ponds), in which both the biomass productivity and lipid content remained stable.72 Whereas sensitivity analysis of single product scenarios (e.g., biodiesel) indicates that higher lipid contents will lead to lower MFSP, the behavior is different in multi product scenarios.69 Therefore, sensibility studies which evaluate on a NPV basis are more appropiate, rather than evaluation of the production cost only (MFSP), because a better valorization of residual process streams can improve the total revenue value. Importantly, in a multi product scenario of biodiesel, glycerin, animal feed, and fertilizer, it was found that a lower biodiesel price was off set by sales of high-value feed and fertilizer and hence the feasibility range based on realistic potential prices for commercial diesel fuel was hardly affected. In other words, the key for biofuels to become price competitive (not cost competitive) is a better valorization of the coproducts. This was also one of the main conclusions of a very recent review on microalgae based biorefinery concepts.72 In sensitivity analysis, the input parameters are based on results from the literature which in turn are based on past events or past interpretations of future outcomes. In this sense, 14037


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volumes of secondary metabolites are very low compared to bulk chemicals and biofuels, their value is much higher, as illustrated in SI Table S2 for astaxanthin, lutein, β-carotene, and phycocyanins. Ruiz et al. designed specific biorefinery process chains for the production of pigments in function of different market scenarios (cosmetics, healthcare, food and natural/synthetic pigments), for example, for the production of omega-3 fatty acid and astaxanthin.27 Based on a realistic cost and market analysis, the authors demonstrated a higher profitability for cosmetic and food related products with better projections for the near future, compared to the production of bulk chemicals and in particular biofuels. Other examples of commercial specialty products from microalgae are PUFAs,75 natural (fluorescent) dyes76 and stable isotope chemicals for research and pharmaceuticals.77 Biofuels in contrast have a relatively low commercial value and need to be produced at large scale or need a better coproduct valorization to become cost and price competitive. These findings has partially moved the interest in algae based research from biofuels to high added-value products.5,21,27,74,75 This shift has also been stimulated by the fall of oil prices.5 Despite various improvements, the selective extraction of valuable compounds remains a key challenge.27 The highest costs are attrituted to biomass drying and cell disruption (e.g., bead-milling, 1 kWh kg−1 ∼ 0.17 USD kg−1 for 95% disruption). The use of pulsed electric fields may drop the energy use to 0.06 kWh kg−1 for 70% cell disruption.78 A lot of energy is also put in solvent extraction and recovery. It was estimated that the use of heat for biomass drying, lipid extraction and solvent recovery reaches 0.21 USD kg−1. Supercritical fluids and switcheable solvent systems are attractive alternatives to traditional solvents. Aqueous ammonia extraction, in similarity with the AFEX process,79 or anhydrous liquid ammonia,79,80 is also an option as ammonia can be recycled efficiently. Ammonia residue streams could be recycled to the algae nutrient feeding.44

switch-value (SV) analysis is more appropiate to compare the financial feasability of biorefinery scenarios in function of a certain input parameter. The parameter values are calculated at which NPV values turn to zero. In other words, SV values describe how close the parameter set for the baseline scenario corresponds with NPV = 0 situations. Doshi et al. (2017) calculated for a multiproduct scenario (biodiesel, glycerol, animal feed and fertilizer) SV values of 19.6 g m−2 day−1 (biomass growth rate), 40% lipids (dry content), 11.8 USD kg−1 (both fertilizer and animal feed price), 41% use of biomass allocated for biodiesel production, 19.5 years (operation period) and 97% use of the LEA residue.69 In the sensitivity analysis, lipid contents higher than the baseline case (40%) resulted in negative NPV values, showing that further improvements in lipid extraction and transesterification are still highly desired before increasing the biomass proportion allocated for biodiesel. By improving the cost-efficiency of these proceses with 20% (via reduced capital investment and maintenance costs), the pay-back period was reduced from 20 to 12.3 years. TEA clusters that explore fast and efficient new scenarios based on novel product and technological developments are highly desired, as recently addressed by an expanded biorefinery superstructure proposed by Rizwan et al., including the processing of microalgae residues and solvent recycling.73 The model (SI Figure S5) was developed for C. vulgaris, but it can easily be extended to other species. 2.7. Market Analysis. Market analysis is an essential part of TEA analysis and should be thoroughly conducted, as it defines the potential market niches, values, and volumes. Microalgae derived products find their market majorly in four sectors: (i) bioenergy and renewable bulk chemicals, (ii) agricultural products (biopesticides and biofertilizers), (iii) animal feed (supplements), and (iv) human use (food, nutraceuticals, and cosmetics). Algal biomass is considered as a suitable feedstock, but the reality is that industrial applications are related to almost exclusively human consumption and animal feed.74 In the bioenergy sector, the production of biofuels requires large scale algal biomass production (ca. 107 tons year−1), which is way too far from the actual global production volume (104 tons year−1). This production scenario also falls short compared to the production required for agricultural (105 tons year−1) and animal feed (106 tons year−1) and only meets the requirements for human applications (104 tons year−1). A market analysis for different microalgae derived products is presented in SI Figure S6. To be economically feasible NPV must be positive, but only products for human consumption and animal feed have market values higher than the production cost. High addedvalue products include animal feed products which are often protein enriched, while products for human consumption are usually obtained from polyunsaturated fatty acids (PUFAs) in lipid fractions and secondary metabolites (i.e., extractives). It is estimated that the market value of carotenoids would reach 1000 million US$ by 2020. Commercially produced astanxanthin from microlalgae has a market value of 15 000 USD kg−1. 2.8. High Added-Value Chemicals. Large scale cultivation plants for the production of biofuels (as described in sections 2.1−2.5)) do not have the same cost distribution, revenue and profitability compared to small-scale specilalized cultivars for the production of high added-value chemicals, as illustrated in a comparison between algal FAME and βcarotene production plants (SI Table S1). Although the market

3. ENVIRONMENTAL IMPACT Most of the environmental impact studies related to microalgae biorefinery scenarios are conducted and evaluated via life cycle analysis (LCA) of carbon, energy, water, and nutrients. The most frequently used environmental sustainability indicators are net energy ratio (NER), greenhouse gas (GHG) emissions and water footprint (WF). Similar to the data from TEA studies, progress is highly desired in further collecting data from pilot plants to estimate better productivity data for large scale plants, and to contrast them with the current available data from large plants.81 3.1. Net Energy Ratio and Greenhouse Gas Emissions. GHG emissions produced during the life cycle of algal biofuels are reported as CO2 equivalents (g CO2eq) by combining CO2, CH4 and N2O emissions scaled by their global warming potentials. NER indicates the ratio of energy demand (from cultivation to final production stage) to energy content of the biofuel. Some works consider only the well to pump cycle (WTP: feedstock terminal and retail station), while others also consider the pump to wheels cycle (PTW: CO2, CH4 and N2O emissions associated with biofuel combustion). Well to wheels (WTW, also ć radle to gravé) results consider the entire biofuel life cycle. Emission data on the combustion of biofuels in engines are still lacking and often the value for low-sulfur diesel is used instead. A substantial amount of the reports in literature used the GREET model (greenhouse gases 14038


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Figure 4. Net energy ratios (NER) and greenhouse gas (GHG) emissions associated with the production of algal derived lipid oil (green), biocrude (blue), and FAME (red).

cultivation are sensitive to several input parameters, some of which are still overlooked.88 Collet et al. (2014) reported recommendations for LCA studies on algal biofuels to harmonize results in order to improve their validity.89 Improvements could be made in the life cycle inventory

regulated emissions and energy use in transportation). This model is updated regularly and can be downloaded as an excel file.82 While most LCA studies on microalgae derived biofuel production reported promising results, others did not.83−87 Clarens et al. (2010) illustrated that life cycle impacts of algae 14039


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Figure 5. NER and GHG emissions associated with the production of algal derived RD production, obtained after hydrotreating of extracted lipid oil (green), HTL biocrude (blue), and pyrolysis oil (red). Gaseous fuels (black) are shown for comparison.

(LCI) and the functional unit itself. At the LCI level, special attention should be paid to the perimeter of the study (e.g., inclusion of infrastructures) and to the valorization of coproducts. 3.1.1. Algal Oil/Biocrude and FAME. Figure 4 shows the high impact scenario variables and the outcome of recent LCA studies on the production of FAME (via transesterification of

lipid oil), algal oil (via DSE/WSE) and biocrude (via HTL). NER and GHG emissions for fossil derived low-sulfur diesel are shown for comparison, as well as the GHG reduction thresholds for 2018 set by the European Directive on Renewable Energy in 2009.97 The general trend for FAME showed a less favorable energy balance (higher NER) and higher GHG emissions, with exception of some scenarios. 14040


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that the impact of the electricity source on GHG emissions corresponds with the same effect as increasing the algal productivity from 10 to 30 g m−2 day−1. This 3-fold increase in productivity would require biochemical and technical developments on the long-term, whereas installing wind turbines and solar panels is more straightforward in the short-term. Positive effects of wind energy on energy balances were also demonstrated by Beal et al. (2015) in scenarios 10e, 10g, and 10i.58 Effects from the nutrient source were also studied. Woertz and co-workers conducted an LCA study on the production of algal biodiesel, in which CO2 and WW were considered as inputs for cultivation (scenario 7).83 The energy demand for CO2 supply and distribution was ca. 17% of the total demand (1.05 × 107 MJ year−1). Based on detailed mass and energy balances, calculated GHG emissions were 70% lower than those of conventional diesel fuel, meeting the minimum 50% reduction requirements set by EPARFS2 and even below the GHG reduction threshold for 2018 set by the European Directive on Renewable Energy.97 GHG emissions from algal biodiesel were estimated at 29 g CO2eq MJ−1, beneath the level for low-sulfur diesel and biodiesel from soya bean (83 g CO2eq MJ−1), at least when taking into consideration also the indirect land use changes. The lower oil content (10%) implies low biodiesel but high LEA yield (LEA was used for the generation of electricity via AD). This case resulted in GHG emissions as low as to 3 g CO2eq MJ−1, showing again the prominent role of the electricity demand in the GHG emission indicator. The energy balance (NER) in turn was high (2.2 MJ per MJ−1 FAME). The authors also quantified the increase in emissions associated with the use of chemical fertilizers. Having a manufacturing GHG emission factor of 3 g CO2eq g−1 nitrogen, emissions increased with 6% with respect to the 89% N recycle case represented in scenario 7, requiring a fertilizer input of 116,250 kg nitrogen year−1. 3.1.2. Algal Renewable Diesel (RD). Figure 5 shows the NER and GHG emissions associated with the production of algal derived biofuels. The general trend is that the results do not vary a lot whether producing FAME or RD. This was confirmed by Zaimes and Khanna (2010) (scenarios 2a−2c in Figure 4 compared to scenarios 4a−4c in Figure 5).91 The impact of the scenario prior to the final conversion step was higher. The results showed that HTL would be the preferred pathway rather than lipid extraction or pyrolysis, at least from an LCA point of view. Frank et al. (2011; 2013) compared RD production obtained either via lipid extraction (scenario 3a) or via HTL (scenario 3b), both followed by HT.90,103 Key variables were the biocrude yield and nitrogen content, along with the hydrogen demand for HT. They concluded that too high HTL yields impedes the valorization of the solid LEA residue via AD (too low C:N ratios). Instead, catalytic hydrothermal gasification (CHG) of LEA to biogas and ammonia was used for the production of CHP in the HTL route. Despite the fact that HTL requires high pressure and temperature, the direct energy use was higher for the WSE route as pressure-homogenization was required in the latter (high electricity demand). The HTL route required ca. 2 times less algal biomass to reach similar RD yields compared to the WSE route. Still, WSE resulted in considerably lower CHG emissions, because after nutrient recycling (NR) from the residual aqueous phase up to 5 times less ammonia and 1.5 times less phosphorus were required additionally, whereas in the HTL process an important amount of nitrogen ends up in

Note that equal biomass productivities and FAME yields can result in different NER and GHG emissions, depending on the carbohydrate and protein contents (coproduct valorization). An important part of the energy and emission balance is related to drying requirements of algal biomass. Whereas HTL requires minimal drying, DSE requires important amounts of energy. DSE scenarios can be improved by integrating heat recovery with the drying process, as illustrated by Zaimes and Khanna (2013) in scenarios 2a-2b, still the WSE method showed better results (scenario 2c).91 Quinn et al. (2014) showed that supercritical CO2 (scenarios 3a-3d), despite having superior extraction performance compared to hexane, was not as favorable as expected.92 This was mainly because it was supposed that CO2 extraction required dry conditions. Soh et al. (2014) conducted LCA studies based on lab-scale (0.5 L) data from 2 freshwater (N. oleoabundans and C. sorokiniana) and 2 marine (N. oculata and T. suecica) microalgal species, both with nitrogen deprivation and repletion (scenarios 4a4h).93 Higher lipid productivity did not lead to lower NER and lower GHG emissions in all cases, because AD also has favorable impacts on these indicators (as drying is not required for AD). Still, considerable uncertainty exists on this effect as the CH4 yields from LEA are poorly described in the literature.83 Ponnusamy et al. (2014) compared hexane extraction in near dry conditions with subcritical water extraction, as a variant to HTL.94 The total energy requirements for subcritical water extraction were estimated similar to those for hexane extraction and recovery (33 MJ kg−1 FAME). For the base case (scenario 5a) they assumed 50% heat exchanger efficiency and 60% in the optimized case (scenario 5b), whereas 85−90% was used in previous literature. The use of external fossil energy is mainly governed by the electricity demand in the cultivation stage for mixing, pumping and injecting gas and can vary widely with considerable effects on both NER and GHG emissions.98,99 It was determined that in the case of Nannochloropsis sp. ORP cultivars, a possible reduction of 70% of the electricity consumption at the cultivation stage would reduce the GHG emissions with ca. 42% (resulting in an emission of 0.85 kg CO2eq) and decrease NER to values below 1.99 In classic ORP cultivars the energy consumption can vary between 0.24 and 1.12 W m−2 or more specifically between 3.7 and 5.7 kWh per kg algal oil.5,99 The reason for this variation is that the main parameter to be optimized during cultivation is the productivity, more than the energy consumption. Microalgae need proper mixing to avoid photoinhibition and photolimitation and to attain high photosynthetic efficiency, for instance by keeping high flow velocities and turbulence levels. Chiaramonti et al. (2013) showed how redesign of raceway ponds can optimize the energy consumption without compromising productivity.100 Another strategy to reduce the input of fossil energy is to increase the share with renewable energy. LCA studies which included renewable electricity as an alternative to grid electricity are rather scarce. Note that in real life situations a photovoltaic energy panel has larger PE compared to most microalgae; the advantage of microalgae is that excess energy can be stored efficiently. Another advantage is that energy consumed on site only has minor transport and distribution losses. Collet et al. (2014) demonstrated how wind turbines and photovoltaic panels could be integrated on site to provide the electricity demand of an 80 ha ORP cultivar.89 At 20 g m−2 day−1 algal productivity, the NER and GHG emissions were reduced with 18 and 21%, respectively. They demonstrated 14041


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evaporation rate, especially in arid regions. Increasing the reutilization of harvest water and the adaption toward seawater input are research areas which deserve further attention.117 The recovery of nutrients from harvest water, which otherwise also would be an environmental burden, also reduces the WF.115 The high impact of freshwater availability in the U.S. on the algae cultivar location was recently demonstrated by Venteris et al.118 Important in the decision taking is the actual salinity of the freshwater source, which should vary close to the salinity of the cultivars to reduce the amount of makeup water. Prospects are therefore strain dependent. The cultivation of microalgae in the vicinity of thermal PP is attractive, not only for CO2 biosequestration but also because PP consume large amounts of cooling water, as recently quantified for China.119 The cooling water could be reutilized for microalgae cultivation and the WW could be treated to use again as cooling water, closing the water cycle. 3.3. Toxicity and Biodiversity in Aquatic Ecosystems. The water quality and consumption are important sustainability indicators of aquatic cultivation systems. They depend on the algal strains used and on the microbial ecology. Many algae species can be grown in low-grade WW to levy pressure on natural freshwater resources.120−122 By doing so, alongside WW remediation credits, it is also possible to procure water and nutrients at lower cost for cultivation at large scale. A wide range of pollutants can be assimilated by microalgae including carbon, NOx, SOx, and heavy metals.4 Microalgae can use both organic and inorganic C, N (in the form of ammonium, nitrate or nitrite) and P. Elevated levels may trigger negative impacts such as algal blooms and oxygen depletion during nights (due to decomposition of dead algae).123 Eutrophication due to accidental release of culture media into the environment is a potential risk for the ecologic biodiversity.124,125 The bioremediation of polluted water streams suffering from algal blooms could generate additional biomass which can be used to increase the biofuel production capacity, provided residual N, P, and S can be controlled properly. Large-scale cultivation of microalgae can be considered as a “controlled eutrophication” process and needs to be well managed by an adequate nutrient supply and by harvesting at regular intervals. 3.4. Wastewater Treatment and Nutrient Recycle. Microalgae cultivation can fit in as a secondary treatment unit in traditional WW treatment facilities, with possibilities to obtain effluents within standards set for surface discharge.51 This approach alleviates negative impacts on the aquatic biodiversity and allows to recover valuable nutrients, which favors the overall energy balance and GHG emissions.87,126 The use of WW not only can reduce the chemical fertilizer demand but it can also minimize the resources needed for chemical WW treatment. Several types of wastewater (WW), produced by municipal (MWW), agricultural (AWW) or industrial (IWW) sources, may be used for microalgae cultivation.126−130 Microalgae based research has demonstrated the potential and the challenges in combining WW nutrient removal and biofuel production.122,131−141 The algae growth is strongly affected by the WW composition and even for the same WW source population dynamics exist.139 SI Table S3 shows the potential of various microalgae strains in different WW treatments. The results show that especially AWW sources provide higher biomass and lipid productivities, which plays in favor of algal farming in rural areas, though MWW sources in nonrural areas may provide nutrients on a larger and more continuous basis. In animal manure effluents, the N:P

the biocrude (5.7 wt % N compared to 0.2 wt % N in WSE lipid oil). The lower GHG emissions in the WSE route were also the result from AD (low heat demand + electricity generation). The scenarios 2a and 2b (WSE route) and 12a and 12b (pyrolysis route) showed high NER and GHG emissions, as in both belt drying was used.102 The effect of drying is also observed by comparing the results in scenarios 1a-1b (for WSE only dewatering required) compared to scenarios 10a−10d (dewatering + thermal drying required for intake in pyrolysis unit). Another example of the impact from drying activities is shown in the scenarios 7a and 7b (HTL, minimal dewatering) and scenarios 11a and 11b (pyrolysis, dewatering + thermal drying).105 By using flue gas as carbon source significant reductions in GHG emissions can be achieved.55,106,107 Rickman et al. (2013) conducted an LCA study on utility-connected systems to evaluate the feasibility of integrating algae cultivars in PP for CO2 biosequestration.108 As considerable energy requirements were associated with pumping of large gas and fluid volumes, the authors pointed out the need of integrated systems which effectively can reduce CO2 emissions. The costs and credits associated with the processing of flue gas is not fully clear in the current literature, some do take these into account and others not. Recently, Laurens (2017) also claimed the urgent need for more detailed studies on how microalgae cultivars could be integrated within or close to existing industrial facilities,5 including PP, natural gas plants, bioethanol and ammonia plants, each of them having different CO2 purities and supply costs.109 3.2. Water Footprint. The water footprint (WF) is the total freshwater quantity embedded in a production scenario, including ground and surface water (blue WF) and rainwater (green WF). This indicator is important, particularly in regions that experience water shortage and aridification risks. The WF depends on the local climate and the actual process design.110 Estimation of the WF is a complex task as it is highly sensitive to evaporation rates and hydraulic retention times. Yang et al. (2011) reported 3727 kg water per dry kg algal biomass.111 A better comparison is based on the water quantity embedded against the energy content of the biofuel produced. WF between 1 and 62 L water per MJ−1 of energy produced were reported.87,112,113 By recirculating harvest water the WF was reduced by 84% and by using seawater it was further reduced to 90%. However, using seawater has indirect effects on MFSP, NER and GHG, as the presence of salt is considered as d́ ead́ mass to be processed. In comparison, the WF of lignocellulosic bioethanol, corn bioethanol and soya biodiesel were estimated at 11−171, 1−18, 2−91 L MJ−1.113,114 Data from pilot-scale reactors (ORP and PBR) operated in three different seasons (summer, fall, and winter) were considered by Pérez-López et al. to evaluate the environmental burdens.115 The energy use for temperature regulation contributed significantly. The production of the high added-value phycocyanin was reported by Papadeki et al., including associated environmental impacts to evaluate the sustainability of the extraction process.116 The recovery of this bioactive compound was highly dependent on the amount of biomass, consumables and energy supplied. Advanced extraction processes such as ultrasound assisted extraction were recommended to decrease the environmental impact. The impact on the water usage from large-scale cultivation of microalgae is still under debate. Introduction of large water volumes at high temperature may have effects on the 14042


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numbers of jobs for pilot plants.5,28 Algae-based industry and rural development can mutually support each other, as land costs in rural areas are lower and biomass transport costs strongly motivates biofuel processing near the algal cultivars.75,149 Depending on whether the project is local or global, the public acceptability may vary.127 Technologies that are accepted in one region may be rejected in other regions. As the large scale algal biobased industry is not established yet, the public acceptability may vary over time. The competition for the use of arable land is an important aspect, often widely discussed in different social communities. Laurens (2017) proposed to perform resource assessment in addition to LCA, quantifying the total amount of product manufactured using a specific process given the amount of input resources (land, water, CO2, and nutrients) available within a specific area.5 These data should indicate how much extra resources should be transported from more distant areas. A study published by Wigmosta et al. (2011) considered the land, water, and resource availability in the U.S., and concluded that ca. 4.3 × 107 ha of available land was suitable for algal cultivation open ponds, which corresponded with a potential production of 2.20 × 1011 L of algal oil per year, equivalent to 48% of the annual petroleum imports in the U.S. (2011).153 It was estimated that 5.5% of U.S. land area would be required in addition to reach these levels of production. The water consumption, however, would exceed 2−3 times the current agricultural water needs. The impact of land use can be minimized to a great extent as algae can be cultivated on marginal lands. However, with regard to temperature and light intensity, many areas identified as suitable for algae cultivation are tropical, where the availability of water is limited and evaporation losses are considerable (arid zones). Concerns still exist in public opinion regarding the use of land for large scale biofuel production.149 Impacts resulting from direct changes (gas flux due to construction of ponds on arable land) and indirect changes (purpose of land used and associated emissions) and the pressure on freshwater availability can be minimized when off-shore cultivation of (macro)algae is implemented. For instance, the “Submariner” research group studied the prospects of associating algae cultivation with an off-shore wind farm in the Baltic sea, with annual algal biomass yields of 1.2 kg per m2 sea surface.154

ratio is so high that it cannot be remediated by crops only, but too high nutrient concentrations in AWW may require dilution first, otherwise it would reduce light penetration considerably.143 Dilution however has a great impact on nutrient removal efficiency, biomass accumulation and lipid productivity.142,144−147 Research has been carried on primary and secondary treated MWW, essentially in activated sludge plants, as well in municipal centrates obtained from the sludge centrifuge. Municipal centrate has been found as an encouraging growth medium, especially for Chlorella which provided the highest lipid productivity reported.131 Industrial WW contains much lower levels of phosphorus and ammonia, and in some occasions it is enriched with heavy metals, which can affect growth rates. Ruiz-Martinez and co-workers studied the removal of N and P from the effluent of a submerged anaerobic membrane bioreactor.144 They used a lab-scale PBR in which algae were cultured in semicontinuous mode for 42 days, assuring stable pH in the growth medium by adding CO2. Despite the variations in N and P concentrations, the anaerobic effluent resulted to be suitable for growing microalgae, with biomass productivities reaching 0.23 g L−1 day−1 and nutrient removal efficiencies of 67 and 98% for NH4+ and PO43− at optimized conditions, respectively. Similarly, submerged membrane photobioreactors (MPBR, see SI Figure S7) were recently reviewed by Luo et al. for microalgae cultivation applied to WW treatment.147 MPBR technology combines conventional PBR with a membrane to allow higher flexibility for WW feed composition and operational conditions. MPBR play an important role in optimization, but the challenge is to avoid fouling which can lead to operational problems. Applying immobilized microalgal technology in MPBRs has the potential to mitigate fouling risks.

4. SOCIO-ECONOMIC IMPACT Data available until-date focus on benefits and hurdles related to the economy of the production process itself, rather than on socio-economic concerns.148 Only a few reviews on the sustainability of microalgae production systems included socio-economic impacts.25,26,149 Qualitative or semiquantitative indicators include social well-being and acceptability. Social well-being refers to fulfilment of basic human needs such as food security and employment. Social acceptability includes factors such as public opinion, transparency, effective stakeholders’ participation, and waste management risks. Recently, a set of more specific socio-economic indicators were proposed by the U.S. Department of Energy:109 food security, employment, ROI, NPV, energy security premium, depletion of nonrenewable energy, fuel price volatility, trade volume, and terms, effective stakeholder participation, transparency, public opinion, income, and works days lost due to injury. The public confidence in the microalgae-based industry is hindered by the lack of reliable information, production transparency, and by the data heterogeneity on health and environmental issues.150 Aspects of public opinion include potential for generating new jobs, odors, esthetical aspects, water usage, recent media reports, perception toward potential use of genetically modified algae, and already established perceptions such as rise in food prices and deforestation associated with first generation biofuels.151,152 One important benefit of setting up an algae-based industry is the projection and creation of new jobs in the farming, refining, and supply sector.149−152 Established algae companies have reported considerable

5. CONCLUSIONS AND FUTURE PROSPECTS Microalgae can play an important role in the development of sustainable production systems. Sustainability is the capacity of a process or system to continue while being able to meet the needs of future generations. In practice, the sustainability of microalgae production systems is evaluated based on technoeconomic assessment (TEA), life cycle analysis (LCA), and socio-economic impact. Recent TEA studies pointed out that current projections for large scale production of microalgal biofuels are not for the near future, due to their low cost competitiveness as compared to fossil fuels and biofuels from other biomass sources. Although the data are highly heterogeneous in nature (depending on the model assumptions and boundaries), the studies agreed on the fact that biomass productivity was the parameter with the highest impact. The high cost is mainly associated with the high energy demand for algae cultivation, harvesting, and drying. Flocculation combined with centrifugation or filtration technology is actually the most cost-effective harvesting method. Conversion methods that directly act on diluted wet 14043


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number: 20161080094) and RUDN University Program 5100.

algae biomass slurry are highly desired to reduce the effect of drying, such as hydrothermal liquefaction (HTL) and anaerobic digestion (AD). In large scale biofuel production, the financial feasibility of multiproduct scenarios is improved signifcantly compared to single product scenarios. The unit production costs of high added-value chemicals are much higher, as they are typically produced in non-optimal growth conditions and at smaller scales. But, these costs are countered by high revenue, and therefore, their commercial production has better projections for the near future. Still, these compounds have limited market niches and volumes at present. LCA of various algal biofuel production scenarios have shown considerable variations, not only depending on the scenario input parameters but also depending on model assumptions and boundaries. Recent studies have demonstrated the positive effect of the integration of renewable energy technologies within algal cultivars to reduce the greenhouse gas emissions emitted during the life cycle of algal biofuels. Whereas in the long-term, algal biotechnology will play an important role in increasing biomass productivity, renewable energy technologies can offer innovative solutions in the short-term. Other imminent algae-based research fields include the integration of cultivation with industrial CO2 point source facilities and the use of wastewaters (WW) and/or seawater to reduce the nutrient requirements and the water footprint. Agricultural WW sources can provide a sustainable nutrient source for cultivation in rural areas, whereas municipal WW may be used for cultivars in urban areas. Finally, as part of the overall sustainable analysis, the socio-economic benefits and burdens require a more uniform and quantified study in the final evaluation.

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LIST OF ACRONYMS AD anaerobic digestion ASPFT advanced supercritical pulverized fuel technology ATS algal turf scrubbers AWW agricultural wastewater BF bioflocculation C centrifugation CHF chitosan flocculation CHG catalytic hydrothermal gasification CHP combined heat and power CAF cationic flocculation DAF dissolved air flotation DSE dry solid extraction FAME fatty acid methyl esters FARM Farm-level Algae Risk Model FPPBR flat panel photobioreactors FT Fischer−Tropsch synthesis GHG greenhouse gas HT hydrotreating HTL hydrothermal liquefaction IGCC integrated gasification combined cycle IWW industrial wastewater LCA life cycle analysis LCI life cycle inventory LEA lipid extracted algal biomass MPBR membrane photobioreactors MWW municipal wastewater NER net energy ratio NGCC natural gas combined cycle NPV net present value NR nutrient recycling ORP open raceway ponds PBR photobioreactors PF pressure filtration PTW pump to wheels PE photosynthetic efficiency PP power plant PPC paddle wheel pond circulation RABR rotating algal biofilm reactor SV switch-value TEA techno-economic assessment TPBR tubular photobioreactors WSE wet solid extraction WTP well to pump WTW well to wheels WW wastewater

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.est.8b02876. (PDF)

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AUTHOR INFORMATION

Corresponding Author

*Phone: +86 10 6278 4701; e-mail: [email protected]. cn. ORCID

Rafael Luque: 0000-0003-4190-1916 Ming Zhao: 0000-0002-5801-5593 Present Address ⊥

Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya str., 117198, Moscow, Russia.

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Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

REFERENCES

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Author Contributions ∥

These authors contributed equally.

Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (grant number: 51506112), Tsinghua University Initiative Scientific Research Program (grant 14044


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