At the initial stage, the team realised that the problem of plastics requires a fundamental rethink which then led to the discovery of new approaches with the potential to transform the current plastic economy. We stumbled upon the concept of the circular economy which aimed to minimise the movement of materials through prior planning of their prospects to be reused and recycled at their end of life, rather than figuring the solution out eventually. For that reason, we investigated alternatives and incorporated a holistic and forward design for our product, the PHBV bioplastic. The team is aware of the potential of the synthetic biology field in addressing a few challenges currently present in PHBV production. Nonetheless, a truly sustainable commercialised production of microbial PHA needs to consider several points of view.
The team was introduced to the concept of Life Cycle Assessment (LCA) which allowed us to measure the environmental impacts of each aspect in a product’s life. With the help of LCA, it is possible to measure the environmental sustainability quantitatively which then can be used to identify the potential hotspots that may contribute negatively to the environment. Different potential scenarios could be assessed as well to allow comprehensive outlook into potential downfalls of the product (or process) itself. From here, the result acquired is further used to develop and design the product into more sustainable environmentally, economically, and socially. Two of our team members have worked on this particular topic with the help of experts on the field aimed to assess the current microbial PHBV production and thus provide alternative solutions to enhance the sustainability of the production itself. The team especially focuses on the industrial stage production as the ultimate goal of this project is commercial microbial PHBV production.
LCA consists of four International Organisation for Standardisation (ISO) approved consecutive stages;
There are two kinds of LCA that are commonly discussed, namely attributional LCA (ACLA) and consequential LCA (CLCA). An ALCA refers to a defined allocation of environmental impacts to a process unit or product, whereas to study wider system effects of change the LCA approach needs to be expanded beyond an ALCA. A CLCA is the method which emphasises on the changes within a system (Jones et al. 2017).
The first scenario involved simulation of microbial PHBV production in 1,000 L scale using glucose from pot ale. The production is divided into three major processes; pot ale pre-treatment using amyloglucosidase from Aspergillus niger (Tokuda 1998), microbial PHBV fermentation (Srirangan et al., 2016, Choi et al. 2002), and PHBV recovery using NaOH (Lee et al. 1999 , Anis et al. 2013).
The goal is to describe the life cycle environmental and energy performance of the PHBV production pathway developed by the team from glucose in the pot ale. The functional unit considered is one kg of dry PHBV granule. The system boundary defined in this study overlooks the whisky production and considers efforts and environmental burden from whisky production to be delinked from pot ale, thus viewing pot ale to be burden free (Gandy & Hinton 2018). We focused on cradle-to-gate life cycle thus only unit operations within the red dotted line boundary are considered. Usage and end-of-life scenarios are not considered in this study either, again due to the boundary. Consequential LCA is performed for this scenario.
Figure 1. The Proposed Boundary for Life Cycle Assessment of PHBV Production in Scenario 1
Data were collected based on the scope specified previously. Most of the datasets applied in this study were acquired from the Ecoinvent v2.0 database and GaBi Professional Database which are largely based on European sites. The rest of data was obtained from literature and simulation using SuperPro Designer.
From the available assessment methods in GaBi ts, the CML method was selected after careful consideration. Four areas of protection are covered namely (i) natural resources, (ii) natural environment, (iii) man-made environment, and (iv) human health. The base line impact categories considered in this study are eutrophication and climate change. Characterisation in CML is based on European and global average values, making it reasonable considering the study is based in the United Kingdom. Normalisation was performed so that the baseline global normalisation factors presented were for the years 1990 and 1995 as cumulative yearly world interventions, whereas weighting was not performed in this method.
Consequential LCA focuses on the prospective future environmental impact caused by alteration in demand of the product. In this case, the demand of pot ale was predicted to increase due to PHBV production which can be supplied from other distilleries or the current distillery by increasing whisky production.
The first impact category was eutrophication potential with 0.322 kg phosphate equivalent per 1 kg PHBV where 99.38% of it comes from wastewater treatment. The rest of it is contributed by process water, ammonia, ethanol, and sodium hydroxide production. This category falls under natural environment area. When wastewater treatment is omitted from the life cycle, the eutrophication potential is 2080 kg phosphate equivalent per 1 kg PHBV potentially due to the present of untreated wastewater produced from unit operations involved. Wastewater treatment is not originally within the system boundary, however this step is necessary and highly recommended as a way to reduce eutrophication potential as shown in this study.
In the second impact category, climate change (specifically global warming potential or GWP) which belongs to human health area, the system is calculated to produce 5.84 kg CO2 equivalent per 1 kg PHBV in 100 year time. The major contributor is again process water production at 36.47% followed by ethanol, ammonia, and sodium hydroxide production, respectively. On the other hand, focusing on land usage change only in this category, the total GWP is 4500 kg CO2 equivalent per 1 kg PHBV in 100 year time whereas the highest contributor is also process water at 80% of the total kg CO2 equivalent followed by sodium hydroxide and ethanol production, respectively. When wastewater treatment is omitted, the total GWP and GWP on land use change only are 5.79 kg and 4410 kg CO2 equivalent, correspondingly.
Figure 2 Life Cycle Assessment Result for Eutrophication Potential and Global Warming Potential of Scenario 1
In addition, the result from impact assessment above does not show which PHBV unit operations have the highest environmental impact potentially due to lack of data available. The major contributors in the categories involved are process water, sodium hydroxide, ammonia, and ethanol production which are indirectly linked to the overall PHBV production (off-sites processes). SuperPro Designer was able to show the power consumption for each unit operation involved as shown in Table 1. The total energy used for 1 kg PHBV was 50.10 kWh with highest power consumption was pre-treatment stage due to its long process.
Table 1 Power consumption of unit operations involved in PHBV production in Scenario 1
Standard Power
kWh/year
kWh/batch
kWh/kg
FR-101 : PHBV Fermentation
8,460.66
143.40
3.41
FR-102 : Seed culture
9.93
0.17
0.00404
DS-101 : PHBV Recovery
4,567.78
77.42
1.84
V-103 : Pot ale Pre-treatment
61,220.95
1,037.64
24.67
DS-102 : Glucose Recovery
20,640.14
349.83
8.32
DS-103 : Disposal treatment
4,530.96
76.80
1.83
DDR-101 : Drum Drying
20.29
0.34
0.00808
Unlisted Equipment
6,215.67
105.35
2.50
General Load
18,647.01
316.05
7.51
TOTAL
124,313.38
2,107.01
50.10
As the consequences of using pot ale in PHBV production, other feedstock alternatives must be considered for animal feed production. Plant-based feedstock has been as an alternative such as barley and oats, however, a number of factors must be considered as well prior to selecting the feedstock to replace pot ale. Firstly, barley and oats are currently used in food and beverage industry. Their demand is predicted to increase if they are also used in animal feed industry, this definitely requires higher barley and oats production to ensure demands from both industries to be met. Secondly, the alternative feedstock should be able to provide similar nutritional value as pot ale to maintain the livestock quality. Thirdly, pot ale has been regarded as burden free in LCA, thus minimising the entire environmental load of animal feed production. Careful consideration must be made before selecting the appropriate feedstock here to prevent build-up in environmental burden of animal feed production.
The second scenario involved simulation of microbial PHBV production in using glucose from draff and pot ale. The production is divided into four major processes; pot ale and draff pre-treatment (White et al. 2017), microbial PHBV fermentation (Srirangan et al. 2016, Choi et al. 2002), PHBV recovery using NaOH (Dietrich et al. 2017) and physical and chemical recycling (Zaverl et al. 2012, Fernandez-Dacosta et al. 2016).
The goal for this scenario is to conduct an attributional LCA to study the environmental impacts of PHBV production starting from draff and pot ale. A secondary goal was to identify the ecological “hot spots” of the modelled process, as well as to quantify the green-house gases (GHG) emissions and the energy consumption of the processes. The functional unit is one kg of dry and granulated PHBV. The system boundaries of the study include the following processes: 1. draff and pot ale preparation, 2. seed culture, 3. fed batch culture, 4. PHBV extraction, 5. chemicals recovery, 6. liquid waste management, 7. solid waste management, 8. PHBV physical recycling scenario, and 9. PHBV chemical recycling scenario.
Figure 3 The Proposed Boundary for Life Cycle Assessment of PHBV Production in Scenario 2
The system boundary of this study omits production of plastic products (bottles, films, etc.), collection, transport, use and sorting and classification of recyclables as these are assumed to be identical to a typical plastic, and will occur regardless of the origin of the plastic. Other assumptions and simplifications made throughout the modelling include;
Attributional LCA was performed on this scenario.
The inventory of the input and output flows of mass and energy for each step of the PHBV production and physical recycling was derived from the mass and energy balances obtained in SPD. Meanwhile, the estimated data for the chemical recycling operation was an adjustment from Fernandez-Dacosta et al., 2016 report. The database used for the model of the production of electricity, heat and water consumption is the Ecoinvent 3.01. British electricity mix, heat and water sources are assumed.
The environmental impact categories of interest for this LCA are: Climate change, abiotic depletion, ecotoxicity, eutrophication and human toxicity. For that reason, the Life Cycle Impact Assessment was done with CML-IA baseline impact method.
The thickness of red lines shown in Figure 4 indicates the severity of the negative impact of each assembly to the LCA. On the other hand, the green lines indicate environmental benefit impacts which can be seen from recycling scenario section. According to Figure 4, recycling process has positive impact to the whole life cycle at -36.8% whereas the downstream or extraction process is the top negative contributor to the life cycle at 106%. Meanwhile in the waste scenario, the assembly of the physical treatment of the PHBV is the number one positive contributors at -70.1%.
Figure 4. PHBV production model visualisation at 35.6% in SimaPro
The analysis of an LCIA can be divided into two levels; the full life cycle and the assembly level. The full life cycle allows the practitioner to make comparisons between the production and the recycling scenario. Conversely, the assembly level grants more opportunity to examine the necessary detail to produce recommendations for the design of the process.
According to the results of the full life cycle of PHBV production, the major environmental impacts are demonstrated by the eutrophication and marine aquatic ecotoxicity categories subsequent to normalisation which shown in the following figure. The production assembly carries the biggest load, whereas the only category that shows positive impacts is eutrophication. Nevertheless, this statement is not sufficient to emit any recommendation of how to manage a decrease.
Figure 5. Normalised impact categories for the full life cycle of PHBV for Scenario 2
The PHBV assembly is composed of the pre-treatment, fermentation and downstream. The characterised results for the PHBV assembly are shown in Figure 6. Furthermore, the individual impact categories were analysed using the same type of results. The PHBV assembly stages are the most significant thus the comparison of the impacts of each process are reported.
Figure 6 Impact categories of the PHBV assembly in Scenario 2
The first category is climate change as implied by Global Warming Potential (GWP) which is related to the emissions of greenhouse gases to air. Having a process where the CO2 emissions are bigger than the CO2 sequestration and removal is a major challenge (Narayan 2011). Having a bioplastic production with a bio-renewable feedstock offers the possibility for a neutral carbon footprint; which would leave the bottleneck to be the design of a process with the lowest greenhouse gas emissions. Figure 7 shows that the downstream processing is contributing a major charge of GWP of the PHBV assembly and to the whole life cycle, as has been previously stated. This is correlated to the high usage of fossil fuel for energy production and thus resulting to the increase in the greenhouse gases generation. It is virtually impossible to achieve carbon neutral PHBV production with the continuous and dependent usage of fossil fuels for energy. Thus, the goal of decoupling plastic production from petroleum can only be attained by the shift to the usage of renewable energy sources throughout the production.
Figure 7 Environmental impacts of the PHBV assembly in the Global Warming Potential category
The cumulative energy demand is a valuable parameter to assess the sustainability performance of a process, rather than only focussing on the impacts generated by the use of substances. The downstream processing entails a great number of operations in this scenario, thus it is not surprising that it contributes the highest impact to the overall life cycle. It must be kept in mind that the results above referred to 1 kg of PHBV. Hence, if an optimal condition of highest cell production and energy optimisation of the downstream processing are achieved then the impacts would consequentially be lowered in an ideal scenario and thus making the whole life cycle more feasible. Correspondingly, the first step to improve the overall PHBV production is to enhance the yield of PHBV produced in fermentation stage and to increase the efficiency of the energy use.
The health risks on the human environment derived from the use of toxic substances in a system are incorporated into the human toxicity category (PreConsultants 2014). This category is one of least reported for LCA studies and we believe that without a doubt is in need of improvement. In terms of synthetic biology, one of the major concerns is the use of genetically modified organism (GMO) and the risks that it entails – risk that is not included in the human toxicity or any other toxicity category. Because of this there are several critics stating that LCA studies are not suitable to evaluate processes using synthetic biology in any of its stages (Seager, et al. 2017). Even if the toxicity impact were actually higher due of the use of GMOs, only fermentation assembly would be reflect such result. For our general purposes, the use of toxic chemicals continues to be a matter of importance as indicated by the downstream stage as can be seen in the Figure 21, rather than the use of GMOs.
Figure 8 Human toxicity potential for PHBV assembly in Scenario 2. The results refer to 1,4-dichlorobenzene equivalent kg emission.
The ecotoxicity potential category indicates the impacts of the release of toxic substances to water and soil (PreConsultants 2014). The downstream processing continues to be the top contributor in the life cycle process that generates most of the environmental impacts. Three sub-categories namely fresh water, marine aquatic and terrestrial are considered here, the normalised results for the complete life cycle showed that the impacts of the marine aquatic ecotoxicity stand out above the rest. Subsequent to further investigation, it was discovered that the contained substances washed in the downstream processing can be identified as the cause of this.
The ecotoxicity category once again failed to include the potential impact of using GMOs in the process. For this reason, the data is presented as an initial point for future work. This limitation is mainly due to the use of pre-existed methods for LCIA. For a better suitability of LCA for SynBio processes, an impact category focusing on the risks of using GMOs (for example, the release of them, the current policies for their use, the problems of reproducibility and mutations in the strains) would be highly recommended to be considered for a more comprehensive analysis.
Figure 9 Ecotoxicity potential for the PHBV assembly. The results are referred to 1,4-dichlorobenzene
This category includes the potential impacts of disposing of macro-nutrients into the environment (PreConsultants 2014). By consulting the inventory for this impact, it can be said that the substance responsible is the ammonia in the system. Even though ammonia is the mainly utilised in the fermentation stage, it is mostly emitted during the downstream process thus resulting to this stage to be the main contributor to the environmental impact in this life cycle as shown in Figure 10.
Figure 10. Eutrophication potential, the results are expressed as kg PO4 equivalents per kg emission
Across all the impact categories described, the downstream processing is perceived to be the biggest contributors to the environmental impacts. This observation corresponds with what has been stated in literature. For this reason a second life cycle assessment was modelled with modified downstream processing which comprise of in-situ secretion system by the E. coli instead of cell disruption method. The LCAs of both processes were compared and the results reported in Figure 11.
Figure 11. Comparison of Life Cycle Assessment of Scenario 2 (Conventional process) and Modified Scenario 2 with in-situ secretion process as part of the downstream stage. The percentage represented in green represents the reductions in the environmental impacts by using the in-situ secretion system.
For all the impact categories in Figure 11, the full life cycle with Scenario 2’s with in-situ secretion process shows a decrease in the environmental impacts through all the categories. This indicates that the use of the in-situ secretion possesses the potential of large beneficial influence in reducing the negative impacts of the downstream processing stage. However, this indication should be taken with a little caution, as further research is still needed. The in-situ secretion system has to be further improved in order to provide a high yield of PHBV outside the cell, as well as the scale-up experiments for this secretion system. However, this path can be addressed using synthetic biology and metabolic engineering tools.
The primary goal of this study was to conduct an attributional LCA to study the environmental impacts of Expanded Polystyrene degradation. A secondary goal was to identify the ecological “hot spots” of the modelled process, as well as quantifying the green-house gases (GHG) emissions and the energy consumption of the process.
The system boundaries of the study (Fig. 10) include the following processes: 1) Blending of Expanded Polystyrene, limonene and ethanol, 2) Filtration, 3) Extraction, 4) Pyrolysis, 5) Distillation, 6) Styrene vaporisation, 7) Batch or media preparation, 8) Fed-batch or fermentation; 8) Disposal scenario of the biomass.
Fig. 11 Proposed Boundary - Detailed flow chart of the model developed for this study for the degradation of 1 kg of Expanded Polystyrene. The boundaries of the system encompass the materials, pre-treatment, pyrolysis, fermentation, and the disposal scenario.
The full Life Cycle network consists of 6560 nodes (see Figure 12). The thickness of the red line shows the negative impact of each assembly to the LCA. In contrast, green lines shows environmental benefit impacts derived from the recycling scenario of the solvents of the disposable scenarios impacts.
Two different analyses were used for the evaluation of this model; CML-IA baseline impact method and Cumulative Energy demand method.
Fig. 12 Life Cycle Assessment using the CML-IA baseline impact method for the model of 1 kg EPS degradation with 0.35% of visualisation.Using the CML-IA methods, in Figure 2 with 0.35% of visualisation, it is clearly that the subassembly of pre-treament is the high contributor to the overall process of EPS degradation. More in detailed, over the categories of Human Toxicity, Ecotoxicity and Global Warming Potential the Pre-treatment subassembly is again the main contributor. However, for Eutrophication the Fermentation assembly the main contributor. By consulting the inventory for this impact, can be said that the substance responsible is the ammonia in the system.
Cumulative Energy Demand Method
The cumulative energy demand is a valuable parameter to assess the sustainability performance of a process, rather than only focussing on the impacts generated by the use of substances. In Figure 3 can be observed that the Pre-treatment processing entails a great number of operations, for that is not surprising that is contributing with highest impact to the overall life cycle.
Figure 14 Life Cycle Assessment using the Cumulative Energy Demand method for the model of 1 kg EPS degradation with 1.5% of visualisation.Recommendations
The percentages for both methods, the CML-IA and Cumulative Energy, pointed the Pre-treatment process as the most expensive in terms of energy demand and environmental impacts, making it susceptible for more study and research for making it more affordable.
In an optimal condition of EPS pyrolysis and energy optimisation of the pre-treatment processing are achieved then the impacts should show a decrease. Making the whole life cycle more feasible. Correspondingly, the second step to improve is the yield of styrene degradation as the current rate is approximately 600 mg/L per 48 hours of fermentation. One possible scenario is the use of only the enzymes for the styrene degradation or couple a bioprocess of production, in that way the charge of energy and materials of the fermentation can be cushioned by the production of a high-value compound.
For the LCA model the three options of Landfill, incineration and composting were evaluated in equal conditions. One of the conclusions is that the option with least environmental impact is the incineration, which could be the chosen option for the final step of Polystyrene degradation process.
One of the most significant findings of this research was the discovery of how much environmental charge from the downstream processing due the amount of water, substances and number of operations. Future work and development focusing in this part of the process to reduce the amounts would help tackling these impacts. The downstream processing probed to be an area of improvement when compared with a process reduced. This hint shows only scratch the surface of how synthetic biology can improve the process. Additionally, another main concern is the dependency of petroleum to reduce the emission of greenhouse gas is vital to shift the use of fossil fuels to renewable sources of energy. Overall, the impacts can be reduced if the efficiency in the production of PHBV is improved.
Increasing the yield of PHBV produced in the fermentation step would potentially result to lesser quantity of materials to be invested for the production of 1 kg of PHBV. Moreover, even when the pre-treatment process does not represent a big charge on the life cycle, a deeper analysis should provide insights on how to improve the productivity for the conversion of lignocellulose to glucose. The use of lignocellulose can increase the savings of greenhouse gas emissions to 90% and 100% (Dietrich et al. 2017), therefore the use of draff and pot ale gives hope in the prospect of lowering greenhouse gases. However, as has been exposed before a future LCA considering the carbon cycle should be performed. Moreover, the use of genetically modified microorganism or crops encloses potential risks for human and environmental toxicity that has not been considered in present LCAs methodologies. Although the GMO used for this study does not represent any explicit harm as the bacteria will remain contained without any interaction with the ecosystem, this does not mean that the ecotoxicity of using GMOs should not be included in the LCA when appropriate.
It is clear that the results of an LCA are highly dependent on the assumptions made. As a measure to evaluate this, there is a need for methods that can investigate the effects of the potential changes introduced by the assumptions. The Monte Carlo analysis evaluates the uncertainty and variability in the input data, assessing the robustness of the LCA results (Curran 2012). It is also important to realise that LCA offers learning and not fixed answers, and that LCA is a process and not a product (Mckone et al. 2011). In terms of sustainability, LCA is designed to aid decision making to assess environmental impacts allowing the users to take measures to reduce such impacts. Coupling LCA with other methods such as Economic Input-Output Analysis, Multi-Criteria Decision Analysis, and Transition Studies, allows the results to be translated to decisions and actions (Røyne 2016).
Note: This wiki entry is part of dissertations submitted as MSc requirement at School of Biological Sciences, The University of Edinburgh.
