Life cycle assessment of bioprocessing schemes for poly(3-hydroxybutyrate) production using soybean oil and sucrose as carbon sources

Resources, Conservation & Recycling 141 (2019) 317–328

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Life cycle assessment of bioprocessing schemes for poly(3-hydroxybutyrate) production using soybean oil and sucrose as carbon sources Ioannis K. Kookosa, Apostolis Koutinasb, Anestis Vlysidisb, a b

T

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Department of Chemical Engineering, University of Patras, 26504 Patras, Rio, Greece Department of Food Science and Human Nutrition, Agricultural University of Athens, Iera Odos 75, Athens 11855, Greece

A R T I C LE I N FO

A B S T R A C T

Keywords: Life cycle assessment Poly(3-hydroxybutyrate) Soybean oil Sucrose Biocomposites

There is a wide variability on the environmental analysis employing life cycle assessment (LCA) of bio-based polymers produced via fermentation especially in the case of poly(3-hydroxybutyrate) (PHB). The main aim of this study is the evaluation of greenhouse gas (GHG) emissions, non-renewable energy use (NREU), acidification potential (AP) and eutrophication potential (EP) of PHB production. These results have been compared with literature-cited studies and petroleum-derived counterparts. The results demonstrate that, apart from methodological issues and shortcomings inherent to the LCA methodology, various parameters (e.g. selection of raw materials, adopted allocation methodology) affect the variability observed in previous studies. It is also demonstrated that PHB production has definite and undisputed advantages over its petrochemical alternatives that are currently produced on a massive scale.

1. Introduction The building materials used in construction range from conventional high-performance engineered structural materials (e.g. glass, steel, cement) and wood-based materials (e.g. glue-laminated materials, plywood) to petroleum-derived plastics (Billington et al., 2015). Although recycling of construction material is generally applied, landfilling is inevitably the end-of-life option for the majority of construction materials. The US Environmental Protection Agency estimated that around 96 million t of construction and demolition waste end up to the annual landfill volume in the USA with the lower performance residential construction material, including polymeric composite material, being around 43 million t of this landfill waste (Billington et al., 2015). The production of plastics increased from 1.5 million t in 1950 to more than 320 million t in 2015 and this is expected to quadruple by 2050 (PlasticsEurope, 2017). In 1998, it was estimated that in the USA the annual plastic consumption as construction material was around 20% of the total consumption, placed only second to packaging applications that amount to 30% of total plastic consumption (Duchin and Lange, 1998). The development of composites as natural fiber reinforced petroleum-derived polymer matrices has attracted significant attention in civil engineering applications. However, the production of plastics from non-renewable resources and the inefficient end-of-life management

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policies that have been adopted for more than 60 years, have already caused critical environmental problems (Shah et al., 2008; Singh et al., 2017). For instance, plastic debris is considered a major threat to marine life as it varies between 60% and 80% of marine debris (Derraik, 2002; Urtuvia et al., 2014; Andrady, 2011). The leakage of plastics into oceans is estimated to be equivalent to dumping the contents of a garbage truck into the ocean every minute and this is expected to become equivalent to 1 truck every 15 seconds by 2050 (World Economic Forum, 2016). The production of biodegradable polymers from renewable resources should be adopted in order to tackle the environmental problems caused by petroleum-derived plastics as proposed by many literature-cited studies (Hrabak, 1992; Byrom, 1992; Lee and Choi, 1998; Suriyamongkol et al., 2007; Koutinas et al., 2014; Ciesielski et al., 2015; Prieto, 2016). In recent years, there is increasing interest on the development of biocomposites with lower environmental footprint than conventional construction materials using biodegradable polymers reinforced with natural fibers (Khoshnava et al., 2017; Dicker et al., 2014). Such biocomposites could be permanent or temporary and used in non-structural or structural applications. Polyhydroxyalkanoates (PHAs) are biodegradable polyesters that are produced intracellularly as energy reserve granules via bacterial fermentation using various industrial waste and by-product streams (Kachrimanidou et al., 2014; Dimou et al., 2015). Among other uses,

Corresponding author. E-mail address: [email protected] (A. Vlysidis).

https://doi.org/10.1016/j.resconrec.2018.10.025 Received 6 March 2018; Received in revised form 21 October 2018; Accepted 22 October 2018 0921-3449/ © 2018 Elsevier B.V. All rights reserved.

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Fig. 1. LCI of soybean oil production.

PHAs can be used in the production of fiber reinforced biocomposites (Khoshnava et al., 2017). The most well-known members of the PHA family are poly(3-hydroxybutyrate) (PHB) and poly(3-hydroxybutyrateco-3-hydroxyvalerate) (PHBV), which are biodegradable within a year, while their physical and mechanical properties resemble those of conventional plastics, such as polyethylene and polypropylene (Byrom, 1992; Suriyamongkol et al., 2007; Ciesielski et al., 2015). The current market share of PHAs remains low mainly due to their high production cost, which is estimated to be 5–10 times the cost of traditional polymers (Lee and Choi, 1998; Van Wegen et al., 1998; Koller et al., 2017). Case specific natural fiber reinforced PHB biocomposites may present similar mechanical properties to wood and engineered wood products and short-fiber reinforced polymer composites employed as construction material (Khoshnava et al., 2017), while in the same time they demonstrate lower environmental impact and ability to biodegrade. A number of Life Cycle Assessment (LCA) studies have concluded that the environmental impact of PHB production, or other biopolymers, can be comparable or even higher to that of conventional polymers produced from petroleum (Gerngross, 1999; Koller et al., 2013; Hohenschuh et al., 2014; Posen et al., 2016; Hottle et al., 2017). The findings of these LCA studies are alarming as they put the main driving forces behind industrial (white) biotechnology into question. The aim of this study is to review critically previous publications on the LCA of PHB production and more importantly to perform a detailed Life Cycle Inventory (LCI) and LCA of PHB production. All intermediate steps and calculations are presented in detail as supplementary material. In addition, researchers will be able to adapt easily the presented

calculations to different raw materials, different geographical areas or incorporate new information or technological advances so as to perform detailed LCA studies on the production of PHAs. Furthermore, the advantages of PHB production over polymer production from non-renewable, petrochemical resources are presented.

2. Materials and methods 2.1. Life cycle assessment This study presents a “cradle-to-gate” assessment using the ISO Standards 14040:2006 and 14044:2006 (ISO, 2006). These Standards define four discrete phases when performing an LCA study: goal and scope definition, inventory analysis, impact assessment and interpretation. In the “goal and scope” phase, the goals of the LCA study should clarify: 1) the intended application of the study, 2) the reasons for implementing the study, 3) the target audience and 4) whether the results will be used in comparative allegations released publicly. The scope refers to qualitative and quantitative information denoting what is included in the study and how it is performed (mainly the product system, the functional unit, the system boundaries and the inventory and impact assessments to be estimated). Modeling the process and collecting all necessary data accounting for energy, material and any other resource consumed or produced within the boundaries of the process set in the previous phase, is referred to as the LCI phase of an LCA study. In the impact assessment phase, the inventory results are translated into impacts on ecosystems, humans or resources with the 318

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aim to assess their importance. This is achieved by applying a series of factors to inventory results to obtain impact estimates, such as NonRenewable Energy Use (NREU), Global Warming Potential (GWP), Acidification Potential (AP) and Eutrophication Potential (EP) (Kookos, 2018). This work presents “cradle-to-gate” LCA studies for the production of 1 kg of PHB, which is considered equivalent to 1 kg of polymer produced from fossil resources. The system boundaries include the production of agricultural crops, their transportation to biotransformation facility, the extraction of raw materials, the fermentation and the recovery of the biopolymer. Emissions that take place during the construction of the production facilities and the machinery and emissions due to administration, maintenance and supervision of their operation are excluded. The “cradle-to-gate” LCA studies for the production of PHB are using either soybean oil or sucrose as fermentation feedstock and evaluate the associated NREU, GHG, EP and AP and compare them with the corresponding impacts of the fossil-based polymers such as high density polyethylene (HDPE) and polypropylene (PP).

as direct and indirect N2O emissions (Huo et al., 2008). The corresponding NREU is 24,295 MJ per t of bioplastic considering that 1.645 t of oil leads to the production of 1 t of bioplastic. The energy content of soybean oil is 39,620 MJ/t, while that of the soybean meal is 9870 MJ/t (Fig. 1). It is important to note that the oil mass is 20.05% of the total mass of products produced, while the energy content of oil is 50.9% of the total energy content of the products. As oil prices are approximately 3 times the price of soybean meal, the soybean oil value is 44% of the value of the products. As the extraction of soybean oil leads to the production of more than one product, to complete the LCI and impact analysis of soybean oil the system boundary should be expanded or, if this is not an option, the environmental burdens to the products should be allocated. The primary choice (i.e. system expansion) when performing an LCA according to ISO standard was excluded due to process complexity, data quality issues and non-intuitive results (Omni Tech International, 2010). The allocation techniques that were studied were allocation based on mass, allocation based on energy and allocation based on value (Tables 1 and 2).

2.2. LCI of soybean oil production

2.3. LCI of PHB production from soybean oil

The system considered for the soybean oil production is shown in Fig. 1. There are three main stages for the production of soybean oil: the soybean cultivation stage, the transportation of soybeans to the oil extraction facility and the soybean oil extraction stage. The main inputs of the soybean cultivation stage are electricity, natural gas, diesel, gasoline and LPG in the form of energy and fertilizers (N, P, K), herbicides, insecticides, seeds and lime while the main output is soybeans and main co-product is aboveground and belowground biomass. The only input of the transportation stage is diesel, which is used as liquid fuel. During the soybean oil extraction process, the soybeans are crushed mechanically and soybean oil is extracted. To improve the yields of soybean oil extraction process, a solvent extraction process is added in order to extract the oil from soybean meal. The standard solvent used is hexane, which is separated from the oil via evaporation and recycled in the process. It is estimated that 2.76 ha of land are required for the production of 1.645 t of soybean oil (which yield 1 t of recovered bioplastic). This is based on data presented by Pradhan et al. (2011) using farm input data from 19 major soybean-growing US states for the period 2006-2010. Pradhan et al. (2011) presented all necessary data for the soybean cultivation system including the weighted average yield (2906.7 kg soybeans/ha). Based on the estimation of 80 km for transportation of soybeans from their production site to the biopolymer manufacturing facility, the inventories up to oil extraction can be estimated. Soybean processing results in the production of 6.378 t of soybean meal and 1.645 t of soybean oil. The calculations presented in Table 1 are based on Pradhan et al. (2011) and have been cross-checked using alternative literature-cited studies (Huo et al., 2008; Omni Tech International, 2010). It has been assumed that the C content that is fixed during cultivation of soybeans is equal to the C content of the two main products from the soybean oil extraction process (soybean oil and soybean meal). Considering that 1.645 t of produced soybean oil contain 77% by weight C and 6.378 t of meal contain 48% by weight C, then it has been estimated that 15.87 t of CO2 have been fixed. As 2.56 t CO2 are emitted in the process of oil production, the net GHG emissions is −13.31 t CO2-eq per t of bioplastic. A significant source of GHG emissions can also be the direct and indirect N2O emissions. However, in this study, the contribution of N2O emissions to GWP has been omitted as there is uncertainty in the conversion of the N contained in soil and water to N2O emissions (Huo et al., 2008). Nonetheless, the direct and indirect N2O emissions from soybean cultivation (above and below ground biomass and use of fertilizers) are contributing only to a small percentage on the GWP of 3.2%, 6.2% and 9.0% when considering mass, energy and value allocation, respectively. This amount was calculated by assuming that 1.325% of the applied N is generated

Data for the biotechnological production of biopolymer from soybean oil are taken from Kahar et al. (2004). The wild-type strain Ralstonia eutropha H16 was cultivated on soybean oil as the only carbon source in a fed-batch bioreactor under phosphorus limitation. After 96 h, 126 g/L of dry cell mass containing 76% (w/w) of PHB homopolymer was obtained achieving a high yield of 0.76 g of biopolymer per g of soybean oil. The recovery of the PHB produced has been achieved using surfactant and hypochlorite (Ramsay et al., 1994) combined with spray drying (Lee and Choi, 1998). The surfactant-hypochlorite method achieves minimum PHB degradation and acceptable recovery (70%–95%). In this study, it is assumed that 80% of PHB recovery is achieved with the surfactant-hypochlorite method, while the cell debris remaining after PHB purification has not been taken into consideration. Moreover, the potential recyclability of the liquid effluent streams resulting from the PHB recovery process has not been considered in this study. The detailed design of the process is presented in the supplementary material. An optimization method for the design of the bioreactor system has been employed (Dheskali et al., 2017). The optimal bioreactor design, according to Dheskali et al. (2017), is obtained by minimizing the total annual cost of PHB produced ($/y). The aim here is to assess the optimal design of the bioreactors in order to determine critical operational parameters that affect the chosen environmental impact categories, such as energy consumption for aeration. The optimization method was a mixed integer non-linear programming problem (Dheskali et al., 2017). The product recovery process was designed based on Lee and Choi (1998). The results of the detailed calculations presented in the supplementary material are summarized in Fig. 2, Tables 3 and 4. The production of 1 t of PHB results in the emission of 4.4 kg CO2-eq per kg of biopolymer and the use of 50.31 MJ of nonrenewable energy per kg of PHB (Fig. 2). Electricity consumption for agitation and aeration of the bioreactors accounts for most of the GHG emissions and energy consumption. CO2 emissions due to cell respiration account for almost one third of the total CO2 emitted by the bioprocess. In addition to the case described above, called the “base case scenario”, an improved processing scenario has been considered where the volumetric productivity in the bioreactors is increased from approximately 1 kg PHB m−3 h−1 to 2 kg PHB m−3 h−1. This scenario is called the “future technology scenario”. In the “future technology scenario”, it has been assumed that all fermentation parameters are equal to the “base case” apart from the productivity which increases from 1 to 2 kg PHB m−3 h−1. This is by no means an unrealistic scenario as volumetric productivities in the range of 4–5 kg PHB m−3 h−1 have been reported 319

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Table 1 LCI for soybean oil production and impact assessment. All data were taken from Pradhan et al. (2011) unless otherwise stated - calculation basis: 1.645 t of oil or 1 t of recovered PHB. Units (per t of PHB)

Agriculture

Transportation

Diesel L 105.17 44.06 Gasoline L 40.43 – LPG L 6.32 – NG Nm3 12.95 – Electricity kWh 54.01 – (grid) Fertilizer N Kg 10.42 – Fertilizer P Kg 38.21 – Fertilizer K Kg 70.74 – Herbicide Kg 5.05 – Insecticide Kg 0.13 – Seeds Kg 217.60 – Lime Kg 1464.46 – Hexane Kg – – Subtotal CO2 sequestered TOTAL Allocated to oil per t of PHB: mass allocation (20.5%) Allocated to oil per t of PHB: energy allocation (50.9%) Allocated to oil per t of PHB: value allocation (44.0%) a b c d

Extraction

Total

GHG emission Factor kg CO2-eq/unit

NREU factor MJ/unit

kg CO2-eq/t PHB

MJ / t PHB

– – – 201.91 401.54

149.23 40.43 6.32 214.85 455.54

2.90a 2.81a 1.70a 2.53a 0.58b

42.50 40.20 26.40 38.90 7.40

433 114 11 544 262

6,342 1,625 167 8,358 3,657

– – – – – – – 20.98

10.42 38.21 70.74 5.05 0.13 217.60 1464.46 20.98

6.08c 3.07c 0.51c 6.00c 13.70 – 0.65d –

51.50 9.20 6.00 319.00 325.00 4.70 0.10 0.50

63 117 36 30 2 – 948 – 2,560 −15,870 −13,310 −2,729 −6,775 −5,856

537 352 424 1,612 41 1,023 146 11 24,295 24,295 4,980 12,366 10,690

calculated. PlasticsEurope (www.plasticseurope.com). Sun et al. (2015). US LCI database.

Table 2 LCI for soybean oil production and impact assessment. All data were taken from Gabi professional database (Gabi, 2015b) unless otherwise stated - calculation basis: 1.645 t of oil or 1 t of recovered PHB. Acidification Potential (AP) Agriculture (kg SO2-eq/unit)

Transportation (kg SO2-eq/unit)

Eutrophication Potential (EP) Extraction (kg SO2-eq/unit)

Diesel 0.924 0.387 – Gasoline 1.074 – – LPG 0.020 – – NG 0.040 – 0.750 Electricity (grid)a 0.250 – 1.859 Fertilizer Nb 0.293 – – b Fertilizer P 1.666 – – b Fertilizer K 0.103 – – c Herbicide – – – Insecticidec – – – Seedsd 3.400 – – Lime 1.390 – – Hexane – – – Soybean – – – Agriculturee Total Allocated to oil per t of biopolymer: mass allocation (20.5%) Allocated to oil per t of biopolymer: energy allocation (50.9%) Allocated to oil per t of biopolymer: value allocation (44.0%) a b c d e

Agriculture (kg P-eq/unit)

Transportation (kg Peq/unit)

Extraction (kg P-eq/unit)

0.229 0.263 0.002 0.007 0.010 0.102 0.103 0.016 – – 2.804 0.188 – 15.419

0.096 – – – – – – – – – – – – –

– – – 0.124 0.073 – – – – – – – – –

Total EP (kg P-eq/unit)

Total AP (kg SO2-eq/ unit) 1.311 1.074 0.020 0.790 2.109 0.293 1.666 0.103 – – 3.400 1.390 – –

0.325 0.263 0.002 0.131 0.082 0.102 0.103 0.016 – – 2.804 0.188 – 15.419

12.156 2.492 6.187 5.349

19.435 3.984 9.893 8.552

PlasticsEurope (www.plasticseurope.com). Patyk and Reinhardt (1997). Assumed that the production and the use including leaching of Herbicides and Insecticides has negligible influence on the AP and EP. Ecoinvent Centre (2008) (assessed for rapeseeds). Renouf et al. (2008).

2.4. LCI of biopolymer production from sugars

in the case of PHB production by Alcaligenes latus cultivated on sucrose (Yamane et al., 1996; Wang and Lee, 1997). The detailed calculations are also presented in the supplementary material and the results are summarized in Table 5. It should be stressed that by doubling the volumetric productivity a significant reduction in the electricity consumption in the bioreactors is achieved. This also reduces GHG emissions to 3.121 kg CO2-eq per kg of PHB and NREU to 32.39 MJ of nonrenewable energy per kg of PHB.

Renouf et al. (2008) have presented a comprehensive LCA study of three sugar producing crops including sugarcane (AUS), corn (USA) and sugar beet (UK). Renouf et al. (2008) have considered the production of unprocessed sugar cane juice that contains fermentable sugars with bagasse as a side stream, which is combusted in a steam boiler for steam production. There are three main stages for the production of

320

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Fig. 2. LCI of PHB production from soybean oil - base case scenario.

fermentable sugar solution from sugarcane: the sugarcane cultivation stage, consisting of cane cultivation, pre-harvest burning and harvesting, the cane transportation stage and milling and juice clarification stage. The main inputs of the sugarcane cultivation stage are fertilizers, lime, pesticides, water, electricity and fuels while the main output is the sugarcane. The only input of the transportation stage is diesel, which is used as liquid fuel. The sugarcane then enters into the sugar mill where it is milled in order to produce the cane juice. Sugarcane bagasse is also produced as a by-product, which is used as a solid biofuel to meet the energy needed for processing the sugarcane. Finally, the cane juice is clarified (93% purity) by using phosphoric acid, flocculants and lime (Renouf et al., 2008). Using the approach of system expansion, Renouf et al. (2008) have estimated the GHG emissions to be approximately 105 kg CO2-eq per t of monosaccharide and the NREU approximately −7,970 MJ per t of monosaccharide produced from sugarcane. The corresponding values for corn-derived glucose are 980 kg CO2-eq per t of monosaccharide and the NREU approximately 6,300 MJ per t of monosaccharide. However, the CO2 that has been fixed during sugarcane cultivation has not been taken into consideration. It has been assumed that the C that is fixed during sugarcane cultivation is equal to the C content of sucrose contained in the sugarcane. To obtain an estimate of the CO2 fixed that can be allocated to sucrose, the C content of sucrose (C12H22O11) is 42.0% by weight. This results in an estimate of

Table 4 AP and EP emissions for the base case with volumetric productivity of 1 kg PHB m−3 h−1 based on experimental data of Kahar et al. (2004) (data given per t of PHB).

Fermentation Electricitya Steamb Cooling Waterb NH3b Subtotal fermentation Biopolymer recovery Electricitya Steamb NaOClc Subtotal recovery Total a b c

AP (kg SO2-eq/ t PHB)

%

EP (kg P-eq/ t PHB)

%

19.334 0.047 0.433 0.062 19.876 12.156 1.565 0.109 0.177 1.851 21.727

88.98 0.22 2.00 0.28 91.48

0.755 0.007 0.180 0.062 1.004 19.435 0.061 0.016 0.027 0.104 1.108

68.12 0.63 16.26 5.58 90.58

7.20 0.50 0.82 8.52 100

5.50 1.44 2.47 9.42 100

PlasticsEurope (www.plasticseurope.com). Gabi professional database (Gabi, 2015b). Ecoinvent Centre (2008).

Table 3 Primary energy use and CO2-eq emissions for the base case with volumetric productivity of 1 kg PHB m−3 h−1 based on experimental data of Kahar et al. (2004) (data given per t of biopolymer). Amount consumed per t of PHB

Fermentation Electricity 4,177 kW h Steam 259 kg Cooling Water 880,000 kg CO2 (respiration) 1,413 kg NH3 52.6 kg Subtotal fermentation Biopolymer recovery Electricity 338 kWh Steam 604 kg Surfactant 247 kg NaOCl 219 kg Subtotal recovery Total a b

GHG emissions factor (kg CO2-eq /unit)

kg CO2-eq / t PHB

%

NREU factor MJ/unit

MJ / t PHB

%

0.576a 0.280a 0.0001b 1.00 1.68b

2,406 73 88 1,413 88 4,068

54.6 1.6 2.0 32.1 2.0 92.32

8.028a 3.950a 0.0016b 0.00 33.8b

33,533 1,023 1,408 – 1,778 37,742

66.7 2.0 2.8 – 3.5 75.02

0.576a 0.280a −0.21b 0.120b

195 169 −51.87 26 338 4,406

4.4 3.8 −1.2 0.6 7.68

8.028a 3.950a 28.200b 2.300b

2,713 2,386 6,965 504 12,568 50,310

5.4 4.7 13.8 1.0 24.98

PlasticsEurope (www.plasticseurope.com). Akiyama et al. (2003). 321

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Table 5 Primary energy use and CO2-eq emissions for the “future scenario” case with volumetric productivity of 2 kg PHB m−3 h−1 based on experimental data of Kahar et al. (2004) (data given per t of PHB). Amount consumed per t of PHB

Fermentation Electricity 1,955 kW h Steam 259 kg Cooling Water 826,000 kg CO2 (respiration) 1,413 kg NH3 52.6 kg Subtotal fermentation Biopolymer recovery Electricity 338 kWh Steam 604 kg Surfactant 247 kg NaOCl 219 kg Subtotal recovery Total a b

GHG emissions factor (kg CO2-eq /unit)

kg CO2-eq / t PHB

%

NREU factor MJ/unit

MJ / t PHB

%

0.576a 0.280a 0.0001b 1.00 1.68b

1,126 73 83 1,413 88 2,783

36.1 2.3 2.6 45.3 2.8 89.2

8.028a 3.950a 0.0016b 0.00 33.8b

15,695 1,023 1,322 – 1,778 19,817

48.5 3.2 4.1 – 5.5 61.2

0.576a 0.280a −0.21b 0.120b

195 169 −51.87 26 338 3,121

6.2 5.4 −1.7 0.8 10.8

8.028a 3.950a 28.200b 2.300b

2,713 2,386 6,965 504 12,568 32,386

8.4 7.4 21.5 1.6 38.8

PlasticsEurope (www.plasticseurope.com). Akiyama et al., 2003.

Table 6 Primary energy use and CO2-eq emissions for PHB production from sucrose (data given per t of biopolymer). Amount consumed per t of PHB

Fermentation Electricity 936 kWh Steam 347 kg Cooling Water 1,680,000 kg CO2 (respiration) 6,500 kg NH3 1,666 kg Subtotal fermentation Electricity 338 kWh Steam 604 kg Surfactant 247 kg NaOCl 219 kg Subtotal recovery Total a b

GHG emissions factor (kg CO2-eq /unit)

kg CO2-eq / t PHB

%

NREU factor MJ/unit

MJ / t PHB

%

0.576a 0.280a 0.0001b 1.00 1.68b

539 97 168 6,500 278 7,582 195 169 −0.052 26 338 7,920

6.8 1.2 2.1 82.1 3.5 95.7 2.5 2.1 −0.7 0.3 4.3

8.028a 3.950a 0.0016b 0.00 33.8b

7,514 1,371 2,688

25.3 4.6 9.0

5,611 17,184 2,713 2,386 6,965 504 12,568 29,752

18.9 57.7 9.1 8.0 23.4 1.7 42.3

0.576a 0.280a −0.21b 0.120b

8.028a 3.950a 28.200b 2.300b

PlasticsEurope (www.plasticseurope.com). Akiyama et al., 2003.

CO2 fixation of approximately −1,540 kg CO2 per t of monosaccharide during sugarcane cultivation. The net GHG emissions are therefore −1,435 kg CO2 per t of monosaccharide. The detailed design of the PHB production process from sucrose is presented in the supplementary material and the results are summarized in Table 6. It is important to note that the GHG emissions are significantly higher in the case of PHB production from sucrose than the case of PHB production from soybean oil. This is mainly due to cell respiration that results in the emission of 6.5 kg CO2 per kg of PHB recovered when sucrose is used. Regarding the non-biogenic CO2 produced during the PHB production process, the sucrose process generates 1,420 kg of CO2-eq per t of PHB which is more than two times lower than the one generated in the base case scenario (2,993 kg CO2-eq per t of PHB) and 17% lower than the one generated in the future scenario (1,708 kg CO2-eq per t of PHB).

(i.e. allocation by mass, by energy and by value). AP (in kg SO2-eq) and EP (in P-eq) associated with the production of soybean oil are shown in Fig. 1 and Table 2. For the production of 1.645 t of soybean oil, 12.156 kg SO2-eq and 19.435 kg P-eq are generated. The cultivation sector (agriculture) is responsible for the 75.4% of AP (9.16 kg SO2-eq) followed by the Extraction and the Transportation sector by 21.4% and 3.2%, respectively. This is mainly due to the production of seeds which accounts for 28.0%, the production and use of phosphorus based fertilizers by 13.7% and the production of lime by 11.4%. Depending on the different allocation methods selected, different AP results are obtained. Allocation by mass (20.5%), by energy (50.9%) and by value (44.0%) gives 2.49, 6.19 and 5.35 kg SO2-eq, respectively, per t of PHB. For the EP, the cultivation sector (agriculture) is even more critical as it is responsible for 98.5% (19.14 P-eq) of the total amount. The main contributor by 79.3% is the “Soybean cultivation” process which is related to the phosphorous leaching due to the use of phosphorus based fertilizers. The leaching has been calculated by assuming a 12.8% runoff as applied phosphorus (Renouf et al., 2008). Moreover, the EP has been also calculated in kg N-eq by using the TRACI 2.1 method assuming a nitrate leaching of 6.5% from the applied N which is the N from aboveground and belowground biomass and the nitrogen coming from N fertilizers (Renouf et al., 2008; Huo et al., 2008). In this way, the EP can be estimated both in kg PO2 eq and in kg N eq and straightforwardly compare the results from this study with literaturecited results. The emissions from soybean oil production were 41.87 kg

2.5. Acidification and eutrophication potential for the different PHB systems Apart from the GHG emissions and NREU for the PHB production from soybean oil, the Acidification Potential (AP) and the Eutrophication Potential (EP) have also been estimated. The latter was assessed by using Gabi v.6 software from PE International (Gabi, 2015a). The LCA methodology that was followed was the CML 2001 method. The mass balances as well as the energy requirements that were used were the same with the ones used for GHG and NREU determination. The same allocation methodologies have been considered 322

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those of fossil-based polymers (see Table 7). The lowest values have been reported by Kim and Dale (2008) partially due to the energy and GHG credits considered. In addition, the authors report significantly lower NREU for the bioreactors and PHB recovery process. Although a number of additional LCA studies for PHB production have been presented in recent years, most of them are based on the results presented in the studies summarized above and report similar results, see for instance Yates and Barlow (2013) and Posen (2016). To conclude, it can be noted from Table 7 that estimations of GHG emissions range from −2.3 to 1.96 kg CO2-eq per kg of PHB, while estimates of NREU range from nearly zero up to 85 MJ kg of PHB. The wide variability might be attributed to shortcomings inherent in the referred LCA studies and to accuracy of the underlying engineering calculations. Although there are several LCA studies that have examined the carbon footprint and the NREU, the number of studies is limited in the case of AP and/or EP (see Table 7). Harding et al. (2007) have implemented a comprehensive LCA study measuring ten impact categories including AP and EP for the production and recovery of PHB from sucrose using the CML 2 Baseline 2000 method. The authors have found that 1 kg of PHB releases 24.9 kg SO2-eq and 5.19 kg PO43− eq. The use of fertilizers and sugar production contribute the most to EP, while steam consumption and sugar production have the highest effect on the AP (Harding et al., 2007). Rostkowski et al. (2012) measured a number of different environmental impacts, apart from AP and EP, for the production of 1 kg of PHB produced from waste biogas using the TRACI 2.0 method. Their cradle-to-gate LCA approach gave an AP equal to 92.5 H + moles and an EP equal to 1.06 kg N-eq. The authors also mentioned that more than 90% for all the calculated impacts were due to the PHB recovery process with solvent extraction. Moreover, the GWP was 942 kg CO2 and the energy requirements 43.52 MJ kg of PHB. The authors also mentioned that biogas can be produced by using the cell debris after the extraction of PHB and the PHB itself after its use and disposal (cradleto-cradle cycle) (Rostkowski et al., 2012). Kim and Dale (2005), apart from GWP and NREU, have also estimated the AP and EP of PHB production and recovery process in a corn grain based system and an integrated system using also the corn stover apart from the grains. The authors calculated 2.14 mol H + eq and 1.90 g N-eq per kg of PHB for the basic system while 0.81 mol H + eq and 1.14 g N-eq per kg of PHB for the integrated system. Alike the current study, the major contributor for EP is corn production while for AP is the biopolymer fermentation and recovery process (Kim and Dale, 2005). Finally, Kendall (2012) has measured the AP and EP per kg of PHB by simulating a hypothetical PHB fermentation process from municipal organic wastes combining different LCI data. The authors assessed an AP range from 16 to 28 g SO2-eq /kg PHB and an EP 0.54–5.0 g-PO43−-eq /kg of PHB (Kendall, 2012).

N-eq per t of recovered PHB where 87.7% of that amount was due to N leaching and 11.1% for the production of seeds. Similarly to AP, different allocation approaches give also different EP results. Mass allocation gives 3.98 kg P-eq and 8.58 kg N-eq per 1.645 t of produced soybean oil (i.e. 1 t of recovered PHB). Regarding the production of PHB including fermentation and downstream purification stages, results for AP and EP are shown in Fig. 2 and Table 4. AP is considerably higher than the soybean production process resulting in 21.7 kg SO2-eq per t of biopolymer as the electricity required for agitation and aeration of the bioreactors contributes to 89% of the PHB fermentation and recovery process. The EP value is notably lower than the one generated from the soybean production process giving 1.11 kg P-eq and 0.67 kg N-eq. It becomes obvious that in the “future” scenario (i.e. doubling the volumetric productivity of PHB) due to the substantial reduction in the electricity consumption by the bioreactors for producing the same amount of PHB, a critical reduction in the AP is observed. It was calculated that AP is reduced by 47.4% (from 21.73 to 11.42 kg SO2-eq) and the EP is reduced by 37.4% (from 1.11 to 0.695 kg P-eq). However, the reduction in EP has minor overall effect as the major contributor for EP emissions, as it has been previously shown, is the cultivation of soybean. Regarding the production of monosaccharides, Renouf et al. (2008) have stated that the AP is around 4 kg SO2-eq per t of monosaccharide, while the EP is 1.66 kg P-eq per t of monosaccharide. As in the “future” scenario, in the case of sucrose usage in the fermentation process, more than 4 times lower electricity is required, and hence, the AP drops even more compared to the “future” scenario. Specifically, it drops by 58.4% from the initial 21.73 kg SO2-eq to 9.04 kg SO2-eq. On the other hand, EP increases as the amount of NH3 required in the case of sucrose fermentation is substantially higher (1,666 kg of NH3 instead of 52.6 kg per ton of PHB recovered). The EP in this case is 2.59 in kg P-eq and 3.00 in kg N-eq. 2.6. Review of previous studies Before presenting the results of our analysis it is considered important to present briefly the results of the most significant studies on the same topic. Gerngross (1999) was the first to perform a LCI for a process producing PHB from renewable resources (corn starch). Gerngross (1999) only calculated the NREU of the process, which was estimated 2.39 kg of fossil fuel equivalent or 84.91 MJ. The latter was obtained by the energy required for production of raw materials (31.22 MJ) and the energy required for the fermentation and downstream process of PHA (2.78 kg of steam and 5.32 kWh of electricity). Akiyama et al. (2003) reported a significantly lower NREU value and also were the first to report values for the GHG emissions. Slightly lower values are reported when soybean oil is used as raw material compared to glucose (see Table 7). Kim and Dale (2005, 2008) and Yu and Chen (2008) also report values for the GHG emissions and NREU lower than

Table 7 GHG emissions, NREU, AP and EP results of previous studies on PHB production (all data are reported per kg of PHB). #

Reference

Raw material

GHG (kg CO2-eq)

NREU (MJ)

AP (kg SO2-eq)

EP (kg P-eq)

1 2 3 4 5 6 7 8 9 10

Gerngross (1999) Akiyama et al. (2003) Akiyama et al. (2003) Kim and Dale (2005) Kim and Dale (2005) Kim and Dale (2008) Harding et al. (2007) Yu and Chen (2008) Rostkowski et al. (2012) Kendall (2012)

Corn starch Soybean oil Corn starch Corn starch Corn starch/stovera Corn starch Sucrose Black syrup from bioethanol plant Biogas Municipal organic wastes

– −0.24 to 0.82 0.48 to 1.39 1.72 to 1.92 −1.15 to −1.19 −2.30 1.96 0.49 942 3.4 to 5.0

84.91 41.88 to 62.13 59.17 to 68.37 66.00 to 68.60 15.80 to 17.80 2.50 41.40 34.00 to 44.00 43.52 55 to 76

– – – 2.14 moles H+ -eq 0.81 moles H+ -eq – 24.9 g SO2-eq – 92.5 moles H+ -eq 16 to 28 g SO2-eq

– – – 1.90 g N-eq 1.14 g N-eq – 5.19 g PO43−eq – 1.06 kg N-eq 0.54 to 5.0 g PO43−-eq

a

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Fig. 3. Comparison of GHG emissions and NREU for PHB and HDPE.

Fig. 4. Comparison of AP and EP for PHB and HDPE. 324

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Fig. 5. Comparison of the GHG emissions and NREU for the base case and “future” technology scenario - PHB production from soybean oil.

3. Results and discussion

reasonable allocation methods are adopted (energy or value) the decrease is significant. For the case of allocation based on energy content the GHG emissions are negative (−2.37 kg CO2-eq/kg of PHB). The production of PHB from sugarcane is even more promising as GHG emissions are decreased further to −2.58 kg CO2-eq/kg of PHB (it should be noted that incineration of PHB will produce + 2.05 kg CO2eq/kg of PHB resulting in a net carbon sequestration of −0.53 kg CO2eq/kg of PHB). This impressive reduction can be attributed to facts that are associated to sugarcane agricultural production and more specifically, as discussed in detail by Renouf et al. (2008), to bagasse combustion for energy supply. As sugarcane production requires virtually no input of fossil fuel energy, sugarcane has an undisputed advantage over other sugar crops. The corresponding figures for the NREU in MJ per kg of polymer are shown in Fig. 3B. The NREU of the fossil-based polymer (HDPE) is estimated (PlasticsEurope, 2014) to be 79.39 MJ/kg of polymer at plant gate (other polymers such as LDPE and LLDPE have similar values). Apart from PHB production from corn derived glucose, which offers no distinct advantage over the production from non-renewable resources, in all other cases considered a significant reduction in the NREU is observed. PHB production from soybean oil results in 21.1% reduction of NREU when energy allocation is used and 30.4% reduction when mass allocation is used. A surplus of energy is observed when PHB is produced from sugarcane (−28.4 MJ/kg polymer) for reasons that have been discussed above. To sum up, PHB production from soybean oil has clear advantages over polymer production from fossil-based raw materials and the advantage is undisputed when the biopolymer is produced from sugarcane. In Fig. 4A and B, the AP and EP results obtained in this study are

The GHG emissions, NREU, AP and EP of PHB production are presented in Figs. 3 and 4. In Fig. 3A, the GHG emissions per kg of PHB are shown and compared with the GHG emissions of a common fossil-based polymer (HDPE), as calculated recently by the Association of Plastic Manufacturers (PlasticsEurope, 2014). PE is produced by polymerization of ethylene, which in Europe is usually produced in the vicinity of refineries, by steam cracking of naphtha and polymerization of the monomers into PE. The emissions of the fossil-based polymer have been compared with the biopolymer produced from soybean oil, sugarcane and corn-derived glucose. In the case of soybean oil, three different scenarios have been evaluated: allocation based on mass, value and energy. The GHG emissions of the fossil-based polymer (HDPE) are estimated (PlasticsEurope, 2014) to be 1.8 kg CO2-eq/kg of polymer at plant gate (other polymers such as LDPE and LLDPE have similar emissions). Only one of the cases considered for PHB production has higher GHG emissions. More specifically, the production of PHB from (US) corn derived glucose results in the emissions of 3.95 kg CO2-eq/kg of PHB at plant gate. This result is in agreement with the conclusions of Gerngross (1999) and is mainly due to the fact that corn production is an energy intensive process, while PHB production from sugars is accompanied by increased CO2 emissions due to cell respiration. The production of PHB from soybean oil results in decreased GHG emissions and the exact figure depends strongly on the allocation methodology selected. When mass allocation is selected, then the GHG emissions are lower than the case of fossil-based polymers, albeit significant (1.67 kg CO2-eq/kg of PHB) and cannot be used to justify any claims for improved performance. However, when the more appropriate and

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improved environmental and economic performance of PHB production. In Fig. 6, the AP and EP results of the base case and “future” scenario for PHB production from soybean oil are presented. AP is affected due to the fact that this environmental impact is strongly associated with the use of electricity. For the base case scenario, the AP for mass and energy allocation are 24.22 kg SO4-eq and 27.92 kg SO4-eq per t of PHB produced, respectively, while the “future” scenario has an AP impact equal to 13.91 kg SO4-eq (mass allocation) and 17.61 kg SO4-eq (energy allocation) per t of recovered PHB. The change in PHB productivity has a minor effect on EP due to the fact that the main contributor for this environmental impact is the soybean cultivation stage and specifically the leaching of phosphorous and nitrogen. The “future” scenario has an EP of 4.68 kg P-eq when mass allocation is used instead of 5.09 kg P-eq (base case) and 10.59 kg P-eq when energy allocation is used instead of 11.00 kg P-eq (base case) per t of PHB.

compared with the ones found in literature-cited studies. AP is not affected by the allocation method selected as the major AP hot spot is the energy requirements during PHB production via fermentation and recovery. The lowest AP impact is caused by using mass allocation (24.22 g SO2-eq/kg PHB) followed by value (27.08 g SO2-eq/kg PHB) and energy (27.92 g SO2-eq/kg PHB) allocation. All three values are close to the AP value reported by Harding et al. (2007) which is equal to 24.9 g SO2-eq/kg PHB produced by sugarcane. PHB produced from organic wastes has also similar AP levels (16–28 g SO2-eq/kg PHB) (Kendall, 2012). For the HDPE production, Boustead (2000) has reported 22.5 g SO2-eq per kg of polymer while plasticsEurope (2008) has measured the AP equal to 6.39 g SO2-eq/kg of HDPE. Regarding the EP, the HDPE has very low values equal to 0.43 g PO43−-eq /kg polymer (PlasticsEurope, 2008) and 0.81 g PO43−-eq /kg polymer (Boustead, 2000) compared to the PHB production. The PHB from soybean oil is significantly affected by the choice of the allocation method as the main contributor is the phosphorous or the nitrogen leaching that occurs at the agricultural stage. The mass allocation method gives an EP of 5.09 g P-eq/kg PHB. This value is very close to the value from sugarcane (5.19 g PO43−-eq/kg PHB) (Harding et al., 2007). However, when the allocation method changes the EP value increases significantly. The energy allocation gives 11.00 g P-eq/kg PHB, while the value allocation gives 9.66 g P-eq/kg PHB. Finally, the EP of PHB produced from organic waste has a value of 0.54 to 5.0 g PO43−-eq/kg PHB (Kendall, 2012). In Fig. 5, the base case scenario is compared with the “future” technology scenario for the case of PHB production from soybean oil with mass and energy allocation. Fig. 5 shows that by doubling the volumetric productivity of biopolymer production as related to the volumetric productivity reported by Kahar et al. (2004), a significant reduction in NREU and an impressive increase in the carbon sequestration are observed. Higher volumetric productivities will lead to

4. Conclusion There is strong evidence that the past and current polymer production and management practices are not sustainable and have already caused irreversible damages to the environment. As their production from unsustainable, fossil-based raw materials and their slow degradation are the main issues of concern, attention has been directed towards the production of biodegradable polymers using renewable resources. Early works that assessed the environmental performance of PHB production raised questions on their ability to achieve sustainable production. This study performed a detailed LCI and LCA of PHB production in order to compare the obtained results with literature-cited publications. The results presented in this study show that the GHG emissions, NREU, AP and EP associated with PHB production depend strongly on

Fig. 6. Comparison of the AP and EP for the base case and “future” technology scenario - PHB production from soybean oil. 326

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the specific renewable raw material used and the allocation methodology adopted. These are also the reasons for the wide variations in the estimations presented in previous publications. However, in order to contribute towards resolving the issue of whether the biotechnological production of PHB is advantageous compared to polymer production from non-renewable resources, Figs. 3–6 show that specific raw materials combined with the use of the most appropriate energy allocation methodology result in estimations for the GHG emissions and NREU that are significantly lower than the estimations available for petroleum-derived polymers. Thus, it is illustrated that PHB production is advantageous compared to its petrochemical counterpart. Furthermore, the investigation of alternative raw materials, especially agricultural residues and side streams from the food industry, could offer several advantages over dedicated crops when combined with the development of integrated biorefineries. Apart from the environmental performance of bioprocesses, there are other important performance metrics that need to be assessed, such as economic and social performance metrics. The academic community needs to work on all these different aspects of the multifaceted problem of evaluating the performance of bioprocesses with the aim to identify the most promising technologies that will bring about the step changes in production technologies that are urgently needed.

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