Socioeconomic indicators for sustainable design and commercial development of algal biofuel systems

Indicators of social well-being

Social well-being denotes fulfilled human needs such as food, health, and shelter. Employment, income, workdays lost to injury, and food security are indicators of social well-being for bioenergy with their units being number of full-time equivalent jobs, household income in dollars per day, average number of workdays lost per worker per year due to injury, and percent change in food price volatility, respectively (Dale et al., 2013a). Employment and food security are particularly important in siting algal biofuel facilities and are discussed below.

Net job creation is often viewed as the principal economic benefit of the algal biofuel supply chain (Zhu et al., 2015). New companies garner political, economic, and social support in a region by projecting the number of hires (e.g., Muradel, 2014). Providing investors with cost-efficient supply chains attracts them to a region and leads to new jobs (Ekşioğlu et al., 2009). Local governments may provide incentives to companies to relocate to an area based on projected hires. Many algal biofuel companies already have reportable employment numbers for pilot plants. Indirect employment (Wei et al., 2010) includes suppliers of resources and technology necessary for algal biofuels, such as nutrients, CO₂, polyethylene liners, PBRs, pumps, as well as personnel from plants that provide colocated resources (e.g., CO₂, nutrients) to biofuel facilities. An analysis of projected employment from the algal diesel sector in China found that employment numbers were sensitive to technical parameters such as biomass productivity, lipid content, project duration, lipid extraction rate, and lipid conversion rate (Yang et al., 2015).

Both employment and household income are indicators of progress toward sustainable algal fuel production that relate to rural development (GBEP, 2011; RSB, 2011). Yang et al. (2015) found considerable variation in projected regional employment in the algal biodiesel sector in China, with model parameters reflecting marginal land resources, temperature, sunlight, and local supply rates of diesel and crude oil. However, given the cost of infrastructure and industrial cultivation expertise required to produce algal biofuels, employment and income indicators are unlikely to be incentives for small landholders (Florin et al., 2014) who may cultivate terrestrial feedstocks. Instead, deployment of enabling technologies may be a prelude to social improvements such as increased employment and income associated with algal-based biofuels in a region. For example, the use of saline water for cultivation might lead to the development of algal biofuel production in regions where freshwater is scarce, such as nonarable regions of Australia, northwestern Africa, the Arabian Gulf, and deserts in the United States (Nair & Paulose, 2014).

Statistics on workdays lost to injury should be available for laboratories and pilot plants, at least for internal company purposes. However, few types of health issues or injuries are specific to algal biofuel production. Potential hazardous scenarios that could lead to workdays lost include algae being dried without mitigations for airborne particulate matter; the use of unfamiliar, toxin-producing algae; risk from volatile organic compounds emitted from unventilated algal cultivation systems; or the use of wastewaters or waste CO₂ streams that lead to accumulation of metals in algal cultivation systems (NRC, 2012, Sullivan, 2013).

Biofuel operations should facilitate ‘the human right to adequate [and nutritious] food and improve food security in food insecure regions’ (RSB, 2011). Measuring food security can be fraught with disagreements about definitions and methodologies (FAO, 1996). Percent change in food price volatility (FAO, 2011) is a potential unit for the food security indicator that would generally be zero if nonagricultural land is used (NRC, 2012; Daroch et al., 2013). Under this constraint, biomass and prices of algae and algal fuel should not be impacted by food price volatility (Ziolkowska & Simon, 2014), nor should they affect it. This result is consistent with the European Union's decision not to impose an indirect land use change factor on algal biofuels (EU, 2012). Nonetheless, it is important to include food security in the set of indicators so that comparative assessments can use a consistent set of indicators.

A possible factor affecting food price volatility could be the use of pastureland, if algal biofuels grown on those lands reduce meat production (NRC, 2012) and if coproducts are not used as feed. Under a scenario where 41.5 × 10⁹ L yr⁻¹ of second-generation biofuels are produced on US pastureland, the most likely land type where both algae grown in open ponds and terrestrial biofuel crops might be deployed, two to five percent of the pastureland could be converted to algae as feedstock (Langholtz et al., 2016). Competition between food crops and algae for fertilizer (Jacquin et al., 2014) could also affect food security if fertilizer is not derived from process waste or wastewater.

Some researchers suggest that algal biofuels could have a net positive impact on food security if defatted, high-protein residual algal biomass is used as a coproduct to replace corn and soybean meal in swine and poultry diets (Gatrell et al., 2014) and if the boundaries of sustainability analyses include coproducts. Food additives for humans, livestock feed, aquaculture food, biochar for fertilizer, polyunsaturated fatty acids, and recombinant protein extracts (e.g., astaxanthin) (Brennan & Owende, 2010; Kiron et al., 2012; NRC, 2012; Austic et al., 2013) are coproducts that could reduce food price volatility. However, this indicator would not capture short-term, temporary disruptions in food supply or contamination (if caused by or alleviated by algal biofuels production), even though they could also have implications for social well-being. Any hypothesized link between algal biofuels and food price volatility cannot be realistically assessed until algal biofuels are in large-scale commercialization.

Indicators of energy security

Another category of socioeconomic progress toward sustainability is energy security, which refers to the relationship between national security and the availability of natural resources for energy. Energy security is one of the primary motivations for the development of algal biofuels, for it provides a response to the need for diversification of energy supply chains (Kirayama & Kajikawa, 2014) and energy supply continuity (Winzer, 2012). During the current early stage of technology development, the flexibility to respond to changing markets, new technologies, and competition is important (Nair & Paulose, 2014). Two indicators of energy security are energy security premium, with units of dollars per gallon of biofuel, and fuel price volatility, with units of standard deviation of monthly percent price changes over 1 year (Dale et al., 2013a). Algal biofuels have the potential to be a hedge against price volatility of diesel, ethanol, or other fuels if they provide a significant fuel source in areas with high fuel imports and flexible supply. Biofuels would not be susceptible to geopolitical challenges that have influenced fossil fuel price volatility and energy security premium in the USA.

Energy security indicators can be classified as ex-post indicators (calculation after price formation in fuel markets) or ex-ante indicators (estimate of future changes in energy security) (Lӧschel et al., 2010). Years or decades are required before ex-post indicators can be measured for algal biofuels. Projecting fuel diversity and market concentration in particular geographic areas (and estimating when and to what extent algal biofuels might make a significant contribution to fuel supply) has substantial uncertainty.

As the most geographically isolated and fossil fuel-dependent US state, Hawaii is at high risk from supply interruptions and fuel price volatility (Bennett et al., 2014). This risk justifies the state's emphasis on renewable energy with a 2030 mandate of 40% of the state's electrical generation being from renewable resources and a concurrent 70% reduction of petroleum use for ground transportation (State of Hawaii, 2013). The climate of Hawaii is suitable for high-productivity algal biofuel production. Therefore, Bennett et al. (2014) estimated land and water resources available across the state and the quantity of potential biofuel that could be produced.

Aviation fuel supply chains have special needs with respect to energy security, including the goal to develop locally based supply chains on every continent, and these fuel supply chains can begin with algae. Furthermore, aviation requires liquid fuels and hence cannot use many other renewable energy alternatives (Dale et al., 2014). Fixed price contracts for aviation fuel are important, but poor timing can result in noncompetitive prices if fossil fuels are used. In addition to political instabilities, fluctuating prices, and decreasing resources, the petroleum supply chain is not sufficiently integrated from production to the airplane, because of geographically distant resources and inefficient transportation by tankers (Nair & Paulose, 2014). Algae production is suited to the need for reliable fuel supplies at many locations around the world. Algal biofuel producers are typically the same companies that produce the feedstock, so supply chain steps are well integrated.

However, threats to the continuous supply of algal biofuels could affect fuel price volatility. Factors include pathogens and predators that cause algae pond crashes and extreme weather events that could affect cultivation. For example, Hurricane Katrina in 2005 in the Gulf of Mexico had a negative effect on energy supply (Reed et al., 2010), and the ability to establish the necessary infrastructure and culture for algae cultivation systems to be able to withstand future disturbances is uncertain.

Indicators of external trade

Two key indicators of external trade (i.e., movement of goods and services across borders) are terms of trade and trade volume. Terms of trade, expressed as percent ratio of price of exports to price of imports, has a value of more than 100% if more capital is coming in from imports than is going out. Trade volume represents net exports or balance of payments and has units of dollars. Prior to large-scale commercialization, algal fuels would likely be used regionally. However, if ethanol were a significant product of a number of algae companies, local surpluses might lead to large-scale exports. New algae projects are sometimes advertised for their ability to improve terms of trade (Muradel, 2014). Until there is commercialization as well as trade, there can be little confidence in projections of trade indicators.

Indicators of profitability

Profitability is an important category of economic sustainability for producers in a nascent industry. Prospects for industry profitability lead to investment capital and help determine which technologies should be pursued through research and development and during scale-up. Key indicators are return on investment (ROI), measured as a ratio or percent (net investment/initial investment), and net present value (NPV) in dollars, the present value of benefits minus costs. Factors that affect profitability and are described below include the cost and availability of infrastructure and capital equipment, availability of resources, productivity, the policy environment, the biofuel system, the price of biofuels, coproducts, and factors affecting the future price of petroleum products (Table 3).

Techno-economic analyses (TEAs) can be used to estimate profitability indicators and to identify factors that affect them. As with other social and economic indicators, profits are not measurable for algal biofuels until the industry grows commercially, but scenario analysis provides estimates. During research and development and at the pilot and commercial scales, TEAs can be performed to compare costs and benefits of a project or facility, to compare multiple technologies, to evaluate how a production target can be met, to identify largest contributors to cost, and to evaluate economically feasible scales of technology implementation. For example, Davis et al. (2015) performed TEAs to determine how to reach a specified biomass cost target (and related productivity target) by 2022. Primary sources of differences in TEA results are differences in cultivation infrastructure, production pathways, financial assumptions, and productivity estimates (Quinn & Davis, 2015). Factors affecting profitability, as identified in TEAs and other studies, are described below. TEAs can be highly uncertain because of a lack of data availability and reliance on parameters extrapolated from laboratory studies and from old data (Slade & Bauen, 2013).

Indicators of resource conservation

Indicators of resource conservation are used where the biofuel supply chain may affect an important resource for sustainability not captured by environmental sustainability indicators, such as water quantity indicators (Dale et al., 2013a). Fossil energy resources are the primary focus, because biofuels substitute for petroleum gasoline and diesel. Also, fossil energy is used to produce algal biofuels in most real or hypothetical systems, but the use of renewable inputs leads to more sustainable systems. Two primary indicators of resource conservation with respect to bioenergy sustainability are depletion of nonrenewable energy resources, with units of MT of petroleum extracted per year, and fossil EROI, the ratio of the amount of fossil energy inputs to the amount of useful energy output in MJ, adjusted for energy quality. Fossil EROI has also been termed the ‘fossil energy ratio’ (Murphy et al., 2011). EROI is recommended by the National Research Council as a first step in assessing the sustainability of an algal biofuel supply chain, because the system must return more energy than it is producing (NRC, 2012). Change in the mass of petroleum extracted per year to support the production of algal biofuels is less commonly measured and is not discussed here.

Fossil EROI considers only fossil energy inputs; solar, wind, and waste biomass used for energy are not included in the denominator because they are renewable resources. Automated technologies used to monitor algae growth, temperatures, and potential harmful strains of algae would facilitate the use of solar photovoltaics in algal biofuel production (Nair & Paulose, 2014). Solar drying is feasible for some algae-based industries but may not be rapid enough for large-scale commercial applications (Sander & Murthy, 2010).

Several studies have estimated EROI for algal biofuels. Most scenarios use fossil energy sources or fossil energy combined with biomass energy, such as biogas. For example, Sills et al. (2013) simulated EROI for algae grown in seawater in hybrid PBR-open-pond systems and found that areal productivities of 34–50 g m⁻² day⁻¹ combined with wet extraction consistently resulted in EROI values >1, while productivities between 17 and 33 g m⁻² day⁻¹ resulted in EROI values greater than one in 75% of Monte Carlo simulations. Zaimes & Khanna (2014) found fossil EROI to be less than one for many algae supply chain scenarios. Beal et al. (2015) simulated scenarios with EROI values between 3.24 and 8.35 that involved gravity-fed volume transfers, airlift pond circulation, naturally settling species, and efficient extraction and conversion processes. Wind power was used in some of their cases. Orfield et al. (2014b) compared EROI of HTL reaction temperatures and times.

Factors that drive energy usage and EROI are listed in Table 4 and depicted with relevant steps in production pathways in Fig. 1. EROI is highly dependent on assumptions of the analysis and boundary choices for supply chains (NRC, 2012), for example, on whether coproducts such as feed are included (Beal et al., 2015).

Infrastructure construction for algal biofuel systems is energy intensive (Lardon et al., 2009). Raceway ponds use less energy than flat-plate PBRs (Weschler et al., 2014). Temperature control of PBRs can require a large amount of energy (Béchet et al., 2014). Energy requirements for cultivation are dominated by pumping and mixing water and sparging (bubbling in) CO₂ (NRC, 2012; Pegallapati et al., 2013). Power consumption increases with mixing speed by about a cube power factor (Benemann & Oswald, 1996).

Synthetic fertilizers comprise a large fraction of energy use in algae cultivation (Clarens et al., 2010). Wastewater use reduces energy requirements, and an energy credit for nutrient removal may be implemented in energy analyses (Sturm & Lamer, 2011). In one study, combining wastewater treatment with algal biofuel production for the two systems, each with EROI less than one, led to an EROI above one (Beal et al., 2012). Energy requirements associated with CO₂ supply can be high (NRC, 2012; Jonker & Faaij, 2013), and fossil EROI is sensitive to the CO₂ source (Borkowski et al., 2012). If flue gas is used, the CO₂ content determines energy requirements of potential separation and transport (Brentner et al., 2011).

Harvesting and dewatering are energy-intensive processes with many options (Mata et al., 2014) that affect EROI (Beal et al., 2015) (Table 4). The pump power consumed for algae harvest is an important determinant of energy consumption (Jonker & Faaij, 2013). Thermal drying processes have a high energy requirement (Razon & Tan, 2011; Sills et al., 2013; Weschler et al., 2014), and fossil EROI is sensitive to these processes (Borkowski et al., 2012).

The most energy-intensive step of algal biodiesel production may be lipid extraction; therefore, energy requirements are sensitive to the type of extraction process (Ponnusamy et al., 2014) (Fig. 1). In example processes, 70–90% of the energy consumption was used for lipid extraction, depending on whether a wet or dry process was involved (Lardon et al., 2009). Wet extraction is a strategy for reducing energy consumption (Lardon et al., 2009). In one study, fossil EROI was linearly dependent on algae lipid content (Mata et al., 2014).

Hydrothermal liquefaction typically has a higher EROI than lipid extraction and transesterification (Beal et al. 2015). In pilot plant measurements, the EROI of HTL processes was around 1.0, but with efficiencies of scale the value could increase to 2.5–3.0 (Liu et al., 2013). Beal et al. (2015) simulated an HTL system with an EROI above eight. Fossil EROI depends on HTL reaction conditions and whether catalytic hydrothermal gasification is used to recover thermal and electrical energy from aqueous phase products (Orfield et al., 2014b).

Energy return on investment is highly sensitive to the fate of residual algal biomass (landfilling vs. anaerobic digestion and biogas production) (Lardon et al., 2009; Brentner et al., 2011; Sills et al., 2013; Dassey et al., 2014). Razon & Tan (2011) estimated a high energy usage for sewage treatment for the biogas effluent. With respect to energy balance, the use of residual biomass in anaerobic digestion may be superior to the production of animal feed as a coproduct (Sills et al., 2013).

Users of fossil EROI should document all energy inputs and outputs and use consistent assumptions in comparisons. How the EROI is calculated can determine whether energy performance is viewed as capable of supporting a sustainable society (Hall et al., 2009) or as ‘marginal to fair’ (Zhang & Colosi, 2013).

Indicators of social acceptability

Social acceptability indicators quantify judgments. Judgments about algal biofuel systems relate to siting, operations, resource use, and fuel use and can be made by any stakeholder group (e.g., local residents, industry leaders, or citizens). Wolfe et al. (2003) defined acceptability as ‘a feasible set of conditions under which the technology would be ‘on the table’ for serious public discussion’. In the algal biofuel context, technologies are already ‘on the table’, and the questions are which technologies and types of facilities have a future.

Social acceptability indicators proposed by Dale et al. (2013a) for bioenergy sustainability include public opinion (percent favorable opinion), transparency (percent of indicators for which timely, relevant performance data are reported), effective stakeholder participation (percent of documented responses addressing stakeholder concerns and suggestions), and risk of catastrophe (annual probability of a catastrophic event). Below, we focus most on factors that affect public opinion. While effective stakeholder participation cannot be projected, we generally address that indicator as well as transparency and risk of catastrophe.

Public opinion could include potential for new employment opportunities, esthetics and odor, recent media reports about algae, perceptions of genetically modified organisms (GMOs) (if used), perceptions of renewable fuels, and perceptions regarding sustainability. Characteristics of algal biofuel production that could affect public opinion are listed in Table 5.

Little information has been published on public opinions of algal biofuels, specifically. Most existing studies of stakeholder perceptions relate to barriers and opportunities that algal fuels provide, rather than concerns about environmental or social effects (Oltra, 2011). An exception is a dialogue among northwestern European algal biofuel stakeholders (industry, nongovernmental organizations, and government institutions) regarding benefits and risks from algal biomass production. Participants in a workshop recommended that nonarable lands should be used for cultivation, GMOs should not be used because of difficulty preventing leakage, and more attention should be devoted to water requirements (Rӧsch et al., 2014).

One consumer trial addressed judgments about fuel. In four cities in California, sustainability factors apparently drove the preferred purchase of a 20% algae-derived biodiesel (Danko, 2013). Sales volume increased 35% at fuel stations offering the algae-derived fuel Ninety-two percent of those surveyed noted that environmental benefits made them likelier to purchase algae-derived fuel, compared to other fuels without those benefits (Propel Fuels, 2013). Forty percent of consumers indicated they would be willing to pay a premium for algae-derived fuels (Danko, 2013), which indicates a high positive public opinion.

Sustainability factors affecting public opinion of bioenergy are pertinent to algal biofuels. Attributes affecting public opinion about Eucalyptus, another bioenergy feedstock, are potential invasiveness and high water use (Dale et al., 2013b). Water scarcity might lead to a poor public opinion of water-intensive bioenergy in locations where current consumptive water use is already close to the available amount (Chaudhry & Barbier, 2013). Potential effects on food prices and deforestation, as well as perceptions of risk of climate change, affected Canadians’ support for advanced biofuel policies (Dragojlovic & Einsiedel, 2015), but food and deforestation issues may be less important determinants of public opinion for algal biofuels. Economic development was a significant factor contributing to the level of community support for a new forest-based biorefinery in Maine, USA (Marciano et al., 2014).

Also important to social acceptability is the extent to which a company's sustainability goals are implemented in facility operations, products, and general strategies (Nair & Paulose, 2014). These goals include safety of operation (Perlaviciute & Steg, 2014) and, therefore, workdays lost to injury (Table 5). Moreover, trust affects social acceptability of energy technologies (Perlaviciute & Steg, 2014).

Perception of a fuel as renewable affects public opinion. The renewable feedstock was an influential variable in determining the level of community support for the forest-based biorefinery in Maine, USA (Marciano et al., 2014). However, in one cross-national study, almost half of respondents did not recognize biomass as a renewable energy source (Devine-Wright, 2003). People evaluate renewable fuels as having lower adverse environmental impacts than fossil fuels, although the environmental effects of concern are not always clear (Perlaviciute & Steg, 2014). Perceived energy independence associated with renewable resources leads to a higher public opinion of them (Culley et al., 2011). Public opinion may be tied to specific biofuels; opinions about corn-based ethanol could be different from those about ethanol (or renewable diesel) derived from algae (Cacciatore et al., 2012).

Place attachment can affect public opinion, depending on whether the project is thought to pose a local threat or opportunity (Devine-Wright, 2007). However, place attachment has been examined in very few renewable energy contexts (e.g., hydropower in Norway, Vorkinn & Riese, 2001).

The use of GMOs in algal biofuel production is expected to grow, especially in PBRs. We are unaware of public opinion surveys that focus on acceptability GMOs for producing algal biofuels. However, the Sustainable Biodiesel Alliance asserts that only biodiesel that is derived from non-GMO feedstock is sustainable (SBA, 2014). Concerns about GMOs in other contexts have been expressed in surveys and the popular press, and concerns about microorganisms (in contrast to plants) relate more to potential environmental effects than to health or ethical issues (Hagedorn & Allender-Hagedorn, 1997). Henley et al. (2013) discussed the probability, albeit low, of released algae altering natural ecosystems. In the USA, anecdotal evidence reveals little unfavorable public opinion regarding uses of GMOs in beneficial products (Glass, 2015). Uncertainty regarding effects of GMOs on the environment and human health is a large concern in developing countries that could affect public opinion of algal biofuels (Adenle et al., 2013). Trust is also important for social acceptability of gene technology (Siegrist, 2000). Some industry and other stakeholders believe that US regulatory review of open-pond uses of GMO algae could impede plans for commercialization, given concerns in the 1980s over outdoor testing of GMOs and current debates over transgenic food crop plants (Glass, 2015). Mesocosm experiments and monitoring of algal cultivation systems could lead to greater understanding of ecological and health risk and to greater public acceptance of the use of GMOs (Henley et al., 2013).

Public perceptions of algae in general, especially in western nations, are sometimes negative. The mention of algae can conjure images of green tides or toxic algal blooms (Jacquin et al., 2014). This perspective is especially pertinent if adverse effects of algae have recently occurred in a region and been covered and potentially exaggerated by the media, for example, Lake Erie ‘being choked each summer by thick mats of algae, much of it poisonous’ (Wines, 2014). Even claims unsupported by science have the potential to affect social acceptability of a nascent industry.

Another indicator of social acceptability is transparency in how indicators are reported. In one study, European algal biofuel experts felt that life cycle analyses lacked transparency regarding data sources (Slade & Bauen, 2013). The study that the US Department of Energy funded to harmonize engineering assumptions for techno-economic modeling of algal biofuels (Davis et al., 2012) was intended, in part, to make the basis for cost estimates be more transparent. If transparency is lacking among scientists and engineers, then it is likely to be lacking among other stakeholders as well.

Effective stakeholder participation is equivalent to what Perlaviciute & Steg (2014) term ‘perceived procedural fairness’. For example, in an effort to make its risk assessment process for GMO algae ‘open and transparent’, the US Environmental Protection Agency is developing a ‘Considerations for Biotechnology Algae’ document (with stakeholder input via a workshop) to clearly describe scientific and technological issues that drive the agency's evaluation of risks from production and use of GMO algae (USEPA 2015b).

Risk of catastrophe can be estimated for well-defined scenarios. For bioenergy sustainability purposes, a catastrophic event has been defined as an event or accident that has more than 10 human fatalities, affects an area greater than 1000 ha, or leads to extinction or extirpation of a species (Dale et al., 2013a,b). Risks to infrastructure, for example, can be estimated based on properties of the materials and frequency of extreme weather events, such as hurricanes. If saline water were extracted, nearby freshwater aquifers could become contaminated (McGraw, 2009), which is why liners are generally required for saline ponds. Where data on risk are not available, indicators might be selected that are related to potential exposure; for example, proximity of cultivation systems to streams or groundwater should relate to risks to aquatic organisms or to humans who drink the water.

The context of a sustainability assessment, including costs and benefits to particular people, is important for assessing social acceptability of energy technologies (Jensen & Andersen, 2013; Perlaviciute & Steg, 2014). While measures may be specific to particular stakeholder groups, to be viable, emerging technologies are generally accepted by producers, markets, the public, and policymakers (Peck et al., 2009). Psychological factors affect how costs and benefits influence acceptability (Perlaviciute & Steg, 2014). Because some technologies will be rejected in some locations and deployed in others (Wolfe et al., 2003), social acceptability indicators are spatially explicit. Moreover, social acceptability of large-scale development of biofuels is hypothetical (Jensen & Andersen, 2013), and social acceptability may change over time (Wolfe et al., 2003). Therefore, these indicators are not as easily modeled as profitability or EROI, which are less sensitive to place and time.