High-Value Propylene Glycol from Low-Value Biodiesel Glycerol: A

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High-value propylene glycol from low-value biodiesel glycerol: A techno-economic and environmental assessment under uncertainty Andres Gonzalez-Garay, Maria Gonzalez-Miquel, and GONZALO GUILLEN GOSALBEZ ACS Sustainable Chem. Eng., Just Accepted Manuscript • Publication Date (Web): 22 May 2017 Downloaded from http://pubs.acs.org on May 22, 2017

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ACS Sustainable Chemistry & Engineering

High-value propylene glycol from low-value biodiesel glycerol: A techno-economic and environmental assessment under uncertainty Andres Gonzalez-Garay, † Maria Gonzalez-Miquel, ‡ Gonzalo Guillen-Gosalbez,*, † †

Department of Chemical Engineering, Centre for Process Systems Engineering, Imperial

College, South Kensington Campus, London, SW7 2AZ, UK ‡

School of Chemical Engineering and Analytical Science, University of Manchester,

Manchester, M13 9PL, UK *Corresponding author: [email protected] (G. Guillén-Gosálbez) KEYWORDS Biodiesel glycerol, propylene glycol, LCA, economic assessment

ACS Paragon Plus Environment

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ABSTRACT

Recent governmental policies that promote a bio-based economy have led to an increasing production of biodiesel, resulting in large amounts of waste glycerol being generated as low-cost and readily available feedstock. Here, the production of high-value bio-based propylene glycol as an alternative chemical route to valorize biodiesel glycerol was studied and assessed considering economic and life cycle environmental criteria. To this end, the conventional industrial process for propylene glycol production, which uses petroleum-based propylene oxide as feedstock, was compared against three different hydrogenolysis routes based on biodiesel glycerol using process modeling and optimization tools. The environmental impact of each alternative was evaluated following Life Cycle Assessment principles, while the main uncertainties were explicitly accounted for via stochastic modelling. Comparison among the various cases reveals that there are process alternatives based on biodiesel glycerol that outperform the current propylene glycol production scheme simultaneously in profit and environmental impact (i.e. 90 % increment in profit and 74 % reduction in environmental impact under optimum process conditions). Overall, this work demonstrates the viability to develop sustainable biorefinery schemes that convert waste glycerol into high-value commodity chemicals, like propylene glycol, thereby promoting holistic bioeconomy frameworks.


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INTRODUCTION The need to develop a more sustainable chemical industry has spurred substantial research for replacing petroleum-based feedstocks by renewable ones1. Several studies have already demonstrated that bio-based chemicals can meet the quality standards required within the industry while at the same time bringing significant environmental benefits when compared with their corresponding fossil-based counterparts2,3. Consequently, different economies around the world are implementing policies and legislations to promote the bioeconomy, which focuses on the use of renewable resources across the industry4,5. Biofuels production has been one of areas with large potential to contribute towards the development of a more sustainable chemical industry. This has led to many regulations seeking to promote their industrialization and commercialization. As a result, large amounts of biofuels have been manufactured over the last years, opening up new opportunities for using their byproducts in other chemical routes (e.g., bio-ethanol derivatives, bio-diesel glycerol, etc.). The use of these molecules as platform molecules in the production of chemicals enhances the so called bioeconomy, while at the same time reduces the use of petroleum-based compounds. Among these by-products, glycerol has received much attention, since it is a highly active molecule with a wide range of applications6. Biomass-based glycerol is generated as by-product in the transesterification of vegetable oils during the production of biodiesel (10 wt. % of total biodiesel production7). Before the biodiesel market took off, glycerol was an expensive chemical seldom used as feedstock. The large amounts of biodiesel glycerol produced in the last decade caused a drastic price drop, stimulating its use as platform chemical (i.e. price for crude glycerol declined from 380 $/ton in 2002 to less than 100 $/ton in 20127). In fact, the fast growth of biodiesel production has resulted in 88% of the global glycerol demand being supplied by this


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process in 20137. Considering that biodiesel production is expected to grow at an estimated annual rate of 10%8, there will be soon a surplus of glycerol supply that the current market cannot accommodate. As a result, exploitation of glycerol as inexpensive, abundant feedstock is receiving increasing attention as an strategy to develop more sustainable processes and products, including valuable bio-based chemicals and novel bio-renewable solvents9–11. The conversion of biodiesel glycerol to propylene glycol (PG) emerges as an appealing alternative, since the market demand of PG can absorb large consumptions of glycerol12. PG is a major commodity across the world having an annual production over 2.18 million tons in 2014 and annual growth of 8%13. The main application for its industrial grade arises in the production of polymers, while the human-safe grade (USP grade) has a wide application as solvent in the food and pharmaceutical industry14 PG is traditionally produced from propylene oxide (PO), which reacts with water to produce PG along with di- and tripropylene glycols. Propylene oxide is a petroleum-based chemical derived by the chlorohydrin or the hydroperoxide processes15. Over the last decade, different studies have analyzed the production of PG from renewable sources such as glycerol, sorbitol or biomass13,16,17. Among these options, catalytic hydrogenolysis of glycerol to PG has been put forward as a sustainable production route and studied under several operating conditions. Some of the alternatives evaluated include systems at high or atmospheric pressure12,18,19, isothermal or non-isothermal conditions12,18–21, external or in situ generated hydrogen20–25 and liquid or vapor phase reactions26–28. However, little focus has been placed on the design and evaluation of the process at an industrial level, which plays a crucial role in the development of a feasible bioeconomy in terms of economic, environmental and social impact.


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Computer-aided process engineering tools enable this type of assessment by estimating the performance of a chemical process via techno-economic analysis, which should ideally account for both economic and environmental criteria at the design stage29–34. In this context, Life Cycle Assessment (LCA) has emerged recently as the preferred tool to quantify the environmental impact of a chemical product, mainly because of its holistic scope that embraces all the material and energy flows taking place across the product’s supply chain35. Unfortunately, chemical processes are subject to different sources of uncertainty that introduce variability into the decision-making problem. Variations in technical, market and supply chain parameters certainly affect the performance of the processes, and the proper understanding of their impact become essential for the success of a sustainable design. The incorporation of uncertainty analysis in the assessment and optimization of more sustainable processes has been addressed in areas such as supply chain management36–38, process synthesis36,39, energy systems40 and water management41, among others. Despite these advances, many techno-economic studies still neglect uncertainties and report nominal values for the economic and environmental performance rather than stochastic ones. Some authors have studied the production of PG from biodiesel glycerol. Posada et al.42 analyzed the economic performance of chemical and biochemical processes that convert glycerol into six different valuable products, concluding that the production of PG represented the best economic option, with a sale price / total cost of production ratio of 1.57. The authors considered the use of external hydrogen at atmospheric pressure, focusing on a standard design with no heat integration and which was not subject to process optimization. Focusing on environmental issues, Adom et al17 found that savings of around 60% in energy consumption and greenhouse gas emissions could be attained in the production of PG by replacing the conventional


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petroleum-based process by hydrogenolysis of bio-based glycerol. The authors, however, provided no details on the specific hydrogenolysis route used in the assessment. Following a different approach and considering another biomass-source of glycerol, Gong and You16 developed a superstructure to assess the use of microalgae as raw material in the production of biodiesel, hydrogen, PG, glycerol-tert-butyl ether and poly-3-hydroxy-ybutyrate. During the assessment, Gong and You considered the use of different routes to produce hydrogen from glycerol as well as external hydrogen. Their analysis, however, is restricted to one single route concerning the hydrogenolysis process. The authors found that when PG is the only bio-product generated, 1.82 kg of CO2 equivalent per kg of PG produced are generated, which represents a reduction of 51.5% compared to the propylene oxide technology. The economic results for this case are nevertheless not reported. It is worthy to mention that none of the previous studies handled uncertainties in their assessments. Focusing on the enhancement of the bioeconomy and the replacement of petroleum-based compounds by renewable feedstocks, we here address the economic and environmental assessment under uncertainty of different routes for the production of PG from biodiesel glycerol. More precisely, three different routes are compared against a benchmark industrial PG technology based on the use of petroleum-derived propylene oxide. The paper is organized as follows. First, we describe the four different routes considered in the assessment. We then introduce the methodology followed and present and discuss the results of the analysis. Finally, the conclusions of the assessment are drawn and the most sustainable route for the production of PG is further discussed. PROCESS DESCRIPTION


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We consider crude glycerol produced from the transesterification of vegetable oils in biodiesel plants. This glycerol usually contains water, methanol, salts and other organic material. In this study, we assume that crude glycerol is purified before it enters any other process by removing methanol, salts and organics, obtaining a feed stream 90 wt. % glycerol and 10 wt. % water43. The liquid feed stream of propylene oxide/glycerol for the proposed cases has a flow rate of 75 kgmole/h. Propylene glycol is produced with 99.5 wt. % purity in all of the cases. A description of the alternatives proposed along with the mechanisms considered for each route is presented next, while further details can be found in Appendix A of the supplementary information. Route business as usual (BAU): Propylene oxide conversion. Figure 1 shows a flow diagram of the standard BAU process, where PG is produced from liquid-phase hydrolysis of propylene oxide (PO) under a non-catalytic reaction14. Propylene oxide and water are mixed according to the ratio 1:1514, since an excess of water is required in the process to limit the generation of by-products dipropylene glycol (DPG) and tripropylene glycol (TPG). The reaction takes place at 18.25 bars and 190 °C, achieving full conversion of PO with a yield of 85 % to PG, 10 % to DPG and 5% to TPG. Distillation columns operate under vacuum at 0.1 bars to avoid decomposition of PG. By-products are recovered with 99.5 wt. % purity in both cases.


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Figure 1. Production of PG from propylene oxide conversion (BAU). Route glycerol-based 1 (GB-1): Isothermal hydrogenolysis at high pressure and external hydrogen. Figure 2 shows the flowsheet of the second route. This alternative follows the twostep mechanism introduced by Pudi et al.44. The reaction is carried out at 205 °C, 20 bars and with a glycerol concentration of 75 wt. %45. The conversion of glycerol reported at these conditions is 88.7 % with a selectivity to propylene glycol of 94.3%. A molar ratio hydrogen/glycerol 5:1 is used in the simulation18. As in the previous alternative, distillation columns operate under vacuum to avoid decomposition of PG. Methanol and ethylene glycol (EG) are generated as by-products and are recovered with 99.5 wt. % purity.

Figure 2. Hydrogenolysis of glycerol at high pressure and isothermal conditions with external hydrogen (GB-1). Route glycerol-based 2 (GB-2): Non-isothermal hydrogenolysis at ambient pressure and external hydrogen. Figure 3 shows the flowsheet of the process. This alternative is based on the work by Akiyama et al.21, following the two-step mechanism presented in alternative GB-1. This option requires a gradient temperature reactor which operates at 200 and 120 °C at the top and bottoms, respectively. Fresh glycerol is not diluted, since Akiyama et al. showed that the


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concentration of glycerol has no impact on the conversion. The molar ratio hydrogen/glycerol is 5:118. Distillation columns operate at atmospheric pressure and by-products methanol and EG are recovered with 99.5 wt. % purity.

Figure 3. Hydrogenolysis of glycerol at ambient pressure and non-isothermal conditions with external hydrogen (GB-2). Route glycerol-based 3 (GB-3): Isothermal hydrogenolysis at high pressure and in situ generated hydrogen. The use of external hydrogen may lead to high operation costs as well as higher environmental impact, since most of it is produced from fossil fuel in refineries. In order to circumvent this limitation, we consider as third alternative hydrogenolysis using in situ generated hydrogen. Figure 4 shows the flowsheet of the process. In the simulation, we implement the reaction mechanism presented by Maglinao et al.20,25, where methanol, ethanol and propanol are generated as by-products. The reaction takes place at 240 °C and 20 bars with a glycerol solution 50 wt. %. Glycerol conversion reported at these conditions is 96% with a yield towards PG of 33%. The liquid products of the reactor are primarily separated into light alcohols (methanol, ethanol and propanol) and heavy alcohols (PG and glycerol). The separation of heavy alcohols is performed under vacuum to avoid degradation of PG. As for the light alcohols, purification is carried out at atmospheric pressure requiring an extractive distillation column,


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since an azeotrope ethanol/propanol/water is formed. Methanol and propanol are recovered with 99.5 wt. % purity while ethanol achieves 99.3 wt. %.

Figure 4. Isothermal hydrogenolysis of glycerol at high pressure with in situ generated hydrogen (GB-3). MATERIALS AND METHODS The full description of the methodology applied to assess each alternative is presented in Appendix B of the supporting information. In essence, a simulation model of each process was first developed using traditional equipment models and then optimized through standard heuristics46, sensitivity analysis and heat integration47. The economic performance and life cycle impact were both assessed afterward considering different uncertainties modeled via Monte Carlo sampling. RESULTS AND DISCUSSION The four processes described above were simulated with Aspen-HYSYS v8.8 using UNIQUAC activity coefficients to model the liquid-vapor equilibrium of the system48. Conversion reactors were defined using stoichiometric data retrieved from different


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sources14,20,21,25,44,45. Process integration is essential to attain sustainable designs and can include heat, mass and property integration. In our assessment, only heat integration was addressed since we considered that the potential savings of mass integration are marginal while property integration had no application to the processes described. We first present the results for the optimized flowsheet of each alternative to later on discuss the uncertainty attached to the models. Energy and mass balances per kg of PG produced are summarized in Table 1. Table 1. Overall mass and energy balances for the production of 1 kg of propylene glycol. Concept

BAU

GB-1

GB-2

GB-3

0.9034

-

-

-

Glycerol solution 90 wt. % (kg)

-

1.4238

1.3707

3.7300

Hydrogen (kg)

-

0.0297

0.0321

-

0.2165

0.0093

-

0.5687

Gas Purge (kg)

-

0.0052

0.0071

2.7926

Wastewater (kg)

-

0.4305

0.3798

0.3205

DPG: 0.1326

Me: 0.0111

Me: 0.0080

Me: 0.0325

TPG: 0.0087

EG: 0.0178

EG: 0.0146

Et: 0.1316

Raw materials Propylene oxide (kg)

Water (kg) Waste streams

Products By-products (kg)

Pr: 0.0165 Energy consumption Electricity (kW)

0.1229

0.0578

0.0582

0.1214

Heating demand (MJ)

11.231

4.635

4.819

16.707

Cooling demand (MJ)

12.640

5.970

6.157

12.288

DPG: Dipropylene glycol; TPG: Tripropylene glycol; EG: Ethylene glycol; Me: Methanol; Et:


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Ethanol; Pr: Propanol. Economic Assessment. The economic performance is quantified using the economic potential (EP/kg of PG) and total annualized cost per kg of PG produced (TAC/kg of PG)49,50. EP is defined as the net profit after taxes while the TAC is the summation of the fixed and variable costs of operation plus an annual capital charge. To express the capital costs on an annual basis, 330 days of operation are considered and the annual capital charge is calculated following a 10year straight line depreciation and considering an interest rate of 15%46. Glycerol price is taken from the current market (0.25 $/kg), while no further subsidies or incentives are considered in the assessment. Further detail of the methodology applied is presented in Appendix B of the supporting information. Raw materials and equipment costs are shown in Tables S12 –S14. Figure 5 displays the contribution to the TAC and the economic potential per kg of PG produced for the alternatives proposed. We identify that all the alternatives generate profit, being alternatives GB-1 and GB-2 the routes with the best economic performance. In terms of the TAC per kg of PG produced, both options present significant reductions when compared to the BAU case (0.679 $/kg of PG for GB-1 and 0.636 $/kg of PG for GB-2 versus 1.781 $/kg of PG in the BAU case). The main reason behind such savings is the difference in price between propylene oxide and glycerol. In the BAU case, the cost of propylene oxide (1.53 $/kg of PG) is already higher than the total cost reported for either process GB-1 or process GB-2. The profit obtained for alternative GB-2 is 1.326 $/kg of PG, which represents an increase of 90% compared to the BAU case. Alternative GB-1 is the second best option with 1.300 $/kg of PG, representing an increase of 86% compared to the BAU case. In contrast, the low yield to PG attained in alternative GB-3 increases the cost per kg of PG by 19% compared to the BAU case (i.e. 2.058 $/kg of PG). Consequently, GB-3 shows a significant decrease in economic potential generating


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only 0.251 $/kg of PG, which corresponds to 36% of the EP/kg of PG obtained in the BAU case (0.700 $/kg of PG). In our assessment, no subsidies nor incentives where considered. However, the significant improvements attained in the economic performance of alternatives GB-1 or GB-2 certainly promote the shift from the current process to the glycerol-based options on a long term basis. In addition, the aim of the industry to boost the bioeconomy and the increasing demand of PG (resulting in the generation of more plants) can further favor the incorporation of the glycerolbased options to the current market.

Figure 5. Contribution to the total annualized cost and economic potential per kg of PG generated. It is worthy to mention that the economic results presented in this assessment differ from those reported by Posada et al.42. More precisely, the ratio commercial sales price/ total cost of production per kg of PG is in our case 4.2 for the best alternative (GB-2), versus 1.57 in their case. The price of PG used in the assessment plays a crucial role in the final value of the


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economic indicator evaluated. As far as we are aware, Posada et al. did not report the PG price used in their assessment, making it hard to carry out a direct comparison of TAC values between their work and ours. We anyway understand that these discrepancies might be due to the use of a non-isothermal reactor (as opposed to the isothermal reactor used in their case), as well as the application of heat integration and sensitivity-based optimization. As an example, the use of a non-isothermal reactor increases the yield of PG from 80% to 98%, yielding savings of as much as 20% in the TAC. Furthermore, high contribution of utilities to the TAC reported by Posada et al. suggests that there was indeed room for improvement in their process via optimization and heat integration. Environmental assessment. To quantify the environmental performance of each alternative, we follow the LCA methodology CML 2001. Glycerol is assumed to be produced from the transesterification of soybean oil in the US. An analysis to validate the impact loads attached to glycerol in the Ecoinvent database is presented in the Appendix C of the supplementary information. Environmental impacts are evaluated per kilogram of PG produced while economic allocation is applied to distribute the total impact of the processes among products and byproducts. Ecoinvent51 v.3.2 database is used to obtain the impact data of streams located beyond the plant boundaries. We assume that purge gas streams are burned, while the liquid waste is immediately sent to a wastewater treatment plant. Entries taken from Ecoinvent database are displayed in Table S2. Figure 6 shows the environmental impact of the different alternatives proposed. As in the economic analysis, alternative GB-2 has the best performance in all the categories, followed by alternative GB-1. When comparing any of these two options against the propylene oxide case, we observe a significant reduction in the environmental impact. The greatest improvement is


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achieved in the category ozone layer depletion with reductions of 89% (1.67·10-6 kg CFC-11eq/kg of PG in the BAU case versus 1.82·10-7 and 1.78·10-7 kg CFC-11-eq/kg of PG for alternatives GB-1 and GB-2, respectively). The lowest improvement is shown in photochemical oxidation, with a drop of 59% in GB-1 and 60% in GB-2 (2.38·10-3 kg CFC-11-eq/kg of PG in BAU versus 9.78·10-4 kg CFC-11-eq/kg of PG in GB-1 and 9.43·10-4 kg CFC-11-eq/kg of PG for GB-2). All the categories are improved on average in as much as 73% in GB-1, and 74% for GB-2. Alternative GB-3 shows the highest environmental impact among the glycerol-based options. This is due to i) the low yield of PG (35% versus 98% in GB-2 and 96 in GB-1), ii) the large amount of emissions generated, and iii) the utilities and equipment necessary to carry out the reaction and separation steps. The potential benefits of these savings on the planet are hard to ascertain since they depend on the extent to which the new technologies might be deployed, their location, transportation routes, logistics, etc. In an attempt to achieve a better appreciation of these savings, we focus next on the category global warming potential, for which specific targets have been pledged to reduce the greenhouse gas emissions by 2020. If we take the production of PG in the US during 2014, the total contribution of PG to the CO2 emissions account for 3.10 million tons of CO2-eq if produced with the BAU case. If we consider the production of PG from one of the glycerolbased options GB-1 or GB-2, the CO2 emissions would account for 1.21 million tons of CO2-eq. Hence, the production of PG from any of the glycerol-based options GB-1 or GB-2 could reduce the CO2 emissions of the chemical sector in the US by 2.79% according to the emissions reported in 2005. The reduction of the total greenhouse gas emission in the US would represent 0.08%. Despite the global benefits are related to global warming mitigation, we would certainly benefit in turn from lower levels of atmospheric pollution causing local impacts.


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With regards to the main contributors of impact, for the BAU case, raw materials entail 94% of the total environmental impact, from which propylene oxide contributes with 99% and water accounts for the remaining 1%. Utilities are responsible for the remaining 6% of the impact, with the heating demand representing 80% of the utilities impact. In options GB-1 and GB-2, based on external hydrogen, raw materials account for 89% of the total impact. In alternatives GB-1 and GB-2, glycerol represents 98% of the raw materials impact, while hydrogen is responsible for the remaining 2%. As for alternative GB-3, based on the in situ generation of hydrogen, the contribution of raw materials is 75%, while utilities represent 21%, steel 1% and waste 3%.

Figure 6. Environmental life cycle assessment results for the proposed alternatives. [Impacts expressed per kg of PG. AP: Acidification potential; GWP: Global warming potential; DAR: Depletion of abiotic resources; FAET: Fresh aquatic ecotoxicity; MAET: Marine aquatic ecotoxicity; TE: Terrestrial ecotoxicity; EP: Eutrophication potential; HT: Human toxicity; OLD: Ozone layer depletion; PO: Photochemical oxidation].


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Note that the reductions in total GHG emissions in GB-1 and GB-2 compared to the propylene oxide case are above those described by Adom et al.17, who reported 8 and 4.5 kg CO2-eq/kg of PG for the propylene oxide case and glycerol option, respectively, versus 4.8 and 1.85 kg CO2eq/kg of PG in our case. Hence, we achieve an impact reduction of 61% (compared to the BAU case) versus 56% in their work. Note, however, that the work of Adom et al. was based on a cradle to grave analysis, while ours is cradle to gate and thus omits end-of-life stages. This difference in scope might explain the discrepancy between the two assessments. Conversely, the value of 1.85 kgCO2-eq for option GB-2 is close to the one reported by Gong and You

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(1.82

kgCO2-eq), who applied a similar cradle to gate LCA study, although in their assessment microalgae are considered as raw material (as opposed to the biodiesel glycerol used in ours). It is worthy to note the use of intensified processes may lead to additional improvements in both economic and environmental criteria. Intensified processes are known to lead to more compact, energy-efficient and environmentally friendly processes. However, they were left out of the analysis because we lack the necessary data for the realistic modeling of such equipment units. Despite obtaining results of the same order of magnitude as other studies, caution must be placed concerning the source of biomass used during the assessment. The use of different types of biomass and/or logistics (e.g. locations of the facilities for the production of soybean oil) may lead to different results. In Table S6 of the supporting information we further assess alternative GB-1 considering five different sources of biomass, showing how different conclusions might be reached depending on the assumptions made. Uncertainty analysis. The process is affected by several technical and environmental uncertainties. To handle them, we first performed a sensitivity analysis over the technical


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parameters (Tables S7 and S8) in order to identify those with the highest impact on the economic and environmental performance. The most critical parameters were found to be the prices of products and raw materials, process conversions and raw materials flowrates. These parameters were then modelled via normal distributions using the mean values and standard deviations shown in Table S8. Furthermore, environmental uncertainties associated with the data retrieved from Ecoinvent51 were modelled following a simplified version of the approach proposed by Weidema and Wesnaes52, which makes use of the Pedigree matrix. More precisely, the life cycle impacts embodied in the inputs to the processes were modelled as lognormal distributions, using the mean values obtained from Ecoinvent and standard deviations (SD) obtained from the Pedigree matrix (and considering the main emission causing the corresponding impact, see Table S10). After modelling all the uncertain parameters, Monte Carlo sampling was applied to generate a set of samples, each entailing a specific set of values of the uncertain parameters and for which the calculations were repeated iteratively. A total of 3,000 samples were generated, ensuring that the mean relative error of the economic and environmental performance indicators would fall below 5% for a confidence level of 95% following the statistical test developed by Law53 (see details in appendix B of the supplementary information). In terms of the mass and energy flows, the uncertainty analysis reveals fluctuations of up to 10% in variables such as PG production and utilities consumption, while by-products and waste streams are more sensitive (from 5% up to 70%). Figure 7 presents the EP/kg of PG and TAC/kg of PG evaluated considering the different uncertainties. Results are displayed using box plots, where the central mark indicates the mean and the bottom and top edges indicate the 25th and 75th percentiles, respectively. The whiskers extend to the most extreme data points within ±2.7


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standard deviations. The results show that the TAC/kg of PG falls in the interval 1.792±15% for the BAU case, 0.695±9% in GB-1, 0.669±12% in GB-2 and 1.888±21% in GB-3. The EP/kg of PG falls in the interval 0.688±35% for the BAU case, 1.285±23% in GB-1, 1.336±22% in GB-2 and 0.393±106% in GB-3. In GB-3, the high fluctuation of EP/kg of PG makes the process economically unappealing in some scenarios. As in the deterministic evaluation, the mean values of the economic indicators present alternative GB-2 as the option with the best performance, followed by cases GB-1, BAU and GB-3. The overall mass and energy balances for all the alternatives under uncertainty are presented in Table S11.

Figure 7. Total annualized cost and economic potential per kg of PG generated under uncertainty. The full LCA results are presented in Figure S6 of the supplementary material. In Figure 8, we display the results of the categories with the highest uncertainty. As in the economic indicators, the central mark indicates the mean value and the bottom and top edges indicate the 25th and 75th percentiles, respectively. The whiskers extend to the most extreme data points within ±2.7 standard deviations. Glycerol-based options GB-1 and GB-2 remained as the best alternatives


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and appear more robust against the environmental uncertainty under the assumptions of the study. In the deterministic evaluation of the environmental performance, alternative GB-2 shows the lowest impact in the 10 categories evaluated. However, when uncertainty in the processes is considered, the mean value of alternative GB-1 slightly outperforms alternative GB-2 in 5 of the 10 categories evaluated. The BAU case and alternative GB-3 show the highest environmental impact and wider distribution among the processes evaluated. In the BAU case, the variation of the results is attributed mainly to the uncertainty in the Ecoinvent data. As for alternative GB-3, the high variation in the environmental categories is attributed mainly to the impact of the conversion in the process. Among the categories, global warming potential shows the lowest variation from its corresponding mean (17 % in BAU, 6 % in GB-1, 6% in GB-2 and 9% in GB3). The largest variation is identified in the category of marine aquatic ecotoxicity (186 % in BAU, 171 % in GB-1, 176% in GB-2 and 169 % in GB-3).


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Figure 8. Environmental life cycle assessment results under uncertainty for the proposed alternatives. Impacts expressed per kg of PG. CONCLUSIONS Herein, four different processes for propylene glycol production have been economically and environmentally evaluated through process simulation and optimization tools along with life cycle assessment. The results presented for the deterministic evaluation of the alternatives show that the use of an external source of hydrogen at atmospheric pressure and gradient of temperatures (GB-2) offers the best glycerol route with potential to increase profitability and reduce the environmental impact (compared to the BAU process) in all the categories evaluated. An additional benefit is the use of atmospheric pressure through all the process. The use of high pressure at isothermal conditions with an external hydrogen source (GB-1) is presented as the


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second best option, leading to a win-win scenario compared to the BAU case but with slightly lower economic potential and environmental impact reduction than route GB-2. The assessment shows that hydrogen has a low contribution towards both the economic and environmental performance. Therefore, the use of in situ generated hydrogen at high pressure (GB-3) presents the worst performance given its low yield towards PG. The recovery of the by-products generated has no significant impact either in economic or environmental terms, while it requires an expensive and complex process configuration. Since all the routes evaluated have shown a high dependence on raw materials, we can conclude that the use of biodiesel glycerol represents a more sustainable route for the production of PG as far as the source of biomass has low environmental impact embodied. Hence, the production of PG from biodiesel glycerol can represent not only a more sustainable option compared to the conventional process, but also an important route to overcome the surplus of glycerol. The uncertainty analysis shows that the most critical parameters are the prices of products and raw materials, conversions of the process and feed flowrates. The economic indicators can vary in as much as 106% from the corresponding mean. Nevertheless, the ranking according to the mean value remains the same as the deterministic evaluation. As for the environmental indicators, variations in as much as 186% from the corresponding mean are observed. Among the alternatives, the results obtained in GB-1 and GB-2 appear more robust against uncertainty than routes BAU and GB-3. Overall, the uncertainty analysis presents alternatives GB-1 and GB-2 as the most appealing routes to be further considered for industrial development. As for alternative GB-3, we advise improvement of the catalytic reaction prior further analysis. Given that the alternatives are based on experimental studies and computer simulations, the results presented still carry a relatively high degree of uncertainty. While consistent with other


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reference studies, a more detailed assessment via pilot plants should be carried out before the scale up of the process. Ultimately, alternative processes like the ones discussed in this article can contribute to boost the bioeconomy, ensure a more sustainable industrial development and address major social, environmental and economic challenges faced nowadays. ASSOCIATED CONTENT Supporting Information. Full description of the alternatives proposed and methodology applied in the assessment, table of prices for the commodities used, environmental entries taken from Ecoinvent database, LCA model for the transesterification process, evaluation of PG production using different biomass sources, technical parameters considered in the sensitivity and uncertainty analysis, data entries and uncertainty basic factors for the evaluation of the Pedigree matrix, equipment characteristics and prices, summary of the mass and energy balances for all the alternatives under uncertainty, economic evaluation under uncertainty and uncertainty graphs for all the environmental categories are included. This material is available free of charge via the Internet at http://pubs.acs.org. AUTHOR INFORMATION Corresponding Author *G. Guillén-Gosálbez. E-mail: [email protected]. Notes The authors declare no competing financial interest. ACKNOWLEDGMENTS


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Gonzalo Guillén-Gosálbez would like to acknowledge the financial support received from the Spanish "Ministerio de Ciencia y Competitividad" through the project CTQ2016-77968-C3-1-P. Andrés González-Garay acknowledge the financial support granted by the Mexican “Consejo Nacional de Ciencia y Tecnologia (CONACyT)”. REFERENCES (1)

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Figure 1. Production of PG from propylene oxide conversion (BAU).


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Figure 2. Hydrogenolysis of glycerol at high pressure and isothermal conditions with external hydrogen (GB-1).


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Figure 3. Hydrogenolysis of glycerol at ambient pressure and non-isothermal conditions with external hydrogen (GB-2).


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Figure 4. Isothermal hydrogenolysis of glycerol at high pressure with in situ generated hydrogen (GB-3).


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Figure 5. Contribution to the total annualized cost and economic potential per kg of PG generated.


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Figure 6. Environmental life cycle assessment results for the proposed alternatives. [Impacts expressed per kg of PG. AP: Acidification potential; GWP: Global warming potential; DAR: Depletion of abiotic resources; FAET: Fresh aquatic ecotoxicity; MAET: Marine aquatic ecotoxicity; TE: Terrestrial ecotoxicity; EP: Eutrophication potential; HT: Human toxicity; OLD: Ozone layer depletion; PO: Photochemical oxidation].


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Figure 7. Total annualized cost and economic potential per kg of PG generated under uncertainty.


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Figure 8. Environmental life cycle assessment results under uncertainty for the proposed alternatives. Impacts expressed per kg of PG.


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TOC We assess the sustainable performance of three different routes for the production of propylene glycol from biodiesel glycerol under uncertainty.


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High-Value Propylene Glycol from Low-Value Biodiesel Glycerol: A

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