Techno-economic and Life-Cycle Assessment of One-Step Production of 1,3-Butadiene from Bioethanol Using Reaction Data under Industrial Operating Conditions

1 Techno-economic and life-cycle assessment of onestep production of 1,3-butadiene from bioethanol using reaction data under industrial operating conditions C.E. Cabrera Camacho† Bernabé Alonso-Fariñas† A.L. Villanueva Perales†* F. Vidal-Barrero† Pedro Ollero† †Departamento de Ingeniería Química y Ambiental, Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Camino de los Descubrimientos s/n. 41092 Sevilla, Spain *Corresponding author email address: [email protected] KEYWORDS Butadiene "This document is the Accepted Manuscript version of a Published Work that appeared in final form in [ACS Sustainable Chemistry and Engineering], copyright © 2020 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acssuschemeng.0c02678 2 Bioethanol Economic assessment Life cycle assessment ABSTRACT A process to produce 1,3-butadiene from ethanol in a one-step reaction with a Hf-Zn catalyst was designed using experimental data from the catalyst performance under industrial conditions, taking into account the presence of water and other by-products in recycled ethanol. The technoeconomic and life cycle assessments of the process were performed and compared to the naphtha-cracking route. In these assessments two scenarios were defined to evaluate the impact of catalyst selectivity (58 and 69%). For the assessment of the environmental sustainability, three further cases were defined to determine the influence of the geographical location of the production plant considering the world’s major ethanol suppliers: The United States, Brazil and Europe. The results of the economic evaluation show that for a plant with a production capacity of 200 ktonne/year of 1,3-BD, and considering an average market price of azeotropic ethanol (450 €/m3), the minimum butadiene selling price for a 10% rate of return on investment ranges 1.13-1.26 times the average butadiene market price (1529 €/tonne). The process can be profitable for favorable combinations of market prices of ethanol and 1,3-butadiene, but the profitability of the process ultimately relies on the development of higher selective catalysts to reduce the consumption of ethanol per tonne of 1,3-butadiene since ethanol dominates the production costs. The LCA shows that switching from naphtha-derived to bio-butadiene can lead to substantial reductions in CO2 emissions (GWP100) (8%-26%) but, in turn, to a significant increase in water consumption (62 to 137-fold) and cumulative energy demand (50-250%). Being that ethanol is 3 the major contributor to all impact categories (65-98% of the impacts), the location of the plant and catalyst selectivity significantly affects the environmental sustainability of the process. Considering the three impact categories and the uncertainty analysis of the LCA results, the best plant location would be Brazil, with a negative median impact value for GWP100 (-73 to -52 kg CO2eq/tonne 1,3-BD) and the lowest median value for blue water consumption (235-299 m3/tonne 1,3-BD) but the highest median value for cumulative energy demand (207-241 GJeq/tonne 1,3-BD), the latter due to the low ethanol yield of sugarcane. INTRODUCTION Nowadays, 1,3-butadiene (1,3-BD) is an important building block for the production of synthetic rubbers and elastomers, such as styrene-butadiene-rubber (SBR), butadiene rubber (BR) and acrylonitrile-butadiene-styrene (ABS), among others1–3. Most 1,3-BD produced worldwide (95%) is obtained as a by-product of the manufacturing of ethylene by the steam cracking of naphtha, while the rest is by the catalytic oxidative dehydrogenation of n-butane and n-butene4–6. Within the context of searching for more sustainable development, the high energy demand and environmental burdens associated with the steam cracking of naphtha justify a renewed interest in the production of 1,3-BD from bioethanol, which is a largelyavailable and renewable resource. Some studies at an early stage of development7,8 showed the potential economic and environmental advantages of 1,3-BD production from bioethanol over naphtha-based 1,3-BD. The catalytic process for the production of 1,3-BD from ethanol at industrial scale was implemented from the 1920s through the 1960s with two main routes of production: the Lebedev process (one-step reaction) and the Ostromisslensky process (two-step reaction)9,10. In the twostep process, ethanol is dehydrogenated to acetaldehyde (eq 1.) in a first reactor and the 4 ethanol/acetaldehyde mixture is converted to 1,3-BD (eq.2) in a second reactor. This allows achieving high selectivity by controlling (i) the temperature at which each reaction takes place and (ii) the ethanol to acetaldehyde molar ratio for (eq 2). In the one-step process, all these reactions (eq 1 and eq 2) take place in a single reactor. The overall reaction (eq 3) is that two molecules of ethanol yield one molecule of 1,3-BD, one molecule of hydrogen and two molecules of water (stoichiometric yield 0.587 tonne 1,3-BD/tonne ethanol). Also, numerous side products are formed6, such as ethylene (eq 4) and diethyl ether (eq 5) from ethanol dehydration, n-butanol from condensation of ethanol (eq 6), butenes from n-butanol dehydration (eq 7), n-butanal from n-butanol dehydrogenation (eq 8) and heavy products (C6+) from successive aldol condensation reactions of aldehydes and ketones (eq 9) formed in other side reactions 11,12. It should be noted that there is not a consensus on the reactions involved in the formation of these side products and here just the simplest side reactions are provided for the reader’s sake. CH3-CH2-OH→CH3-COH + H2 (eq 1) CH3-CH2-OH+CH3-COH→CH2=CH-CH=CH2+2H2O (eq 2) 2CH3-CH2-OH →CH2=CH-CH=CH2+H2+2H2O (eq 3) CH3-CH2-OH→CH2=CH2+H2O (eq 4) 2CH3-CH2-OH→CH3-CH2-O-CH2-CH3 + H2O (eq 5) 2CH3-CH2-OH→CH3-CH2-CH2-CH2OH+H2O (eq 6) CH3-CH2-CH2-CH2OH→ CH2=CH-CH2-CH3+H2O (eq 7) 5 CH3-CH2-CH2-CH2OH→ CH3-CH2-CH2-COH+H2 (eq 8) Aldehydes/ketones →C6+ products (eq 9) The one-step process was developed in Russia, while the two-step process was developed in the USA and commercialized by Union Carbide and the Carbon Chemical Corporation. Both technologies became economically unfeasible due to the development of routes to produce 1,3- BD from petroleum-derived naphtha5,9,13, with the exception of China and India, where they are still marginally used6. Since the cost of ethanol dominates the production costs, as concluded in this work, the most effective way to enhance the competitiveness of the process is to develop more selective catalysts in order to reduce consumption of ethanol per kg of 1,3-BD. That is the reason why in the last decade, the renewed interest in the production of 1,3-BD from ethanol has fostered the research of more selective and stable catalysts through a better understanding of reaction mechanisms, the required acid/base feature of the catalyst, the impact of preparation methods and the effect of reaction conditions2,11,14–16. Despite the great advance in catalyst development, the literature on the techno-economic and environmental assessment of one- and two-step processes based on this new generation of catalyst is scarce1,17,18. Only one techno-economic assessment (TEA) of the one-step process has been published17, in the context of a bio-refinery with two parallel production lines, one for 1,3-BD and another for ԑcaprolactam, both using C6 sugars as raw material and sharing a combined heat and power (CHP) system. The authors concluded that, for two different catalysts, an Au/MgO/SiO2 catalyst2, and an undisclosed catalyst, with 66 and 48% 1,3-BD selectivity, respectively, the 1,3- BD production is not economically viable since the production costs are 3-5 times higher than their reference market price (900 €/tonne). Regarding the environmental assessment of the one- 6 step process, Shylesh et al.2 evaluated the cradle-to-grave greenhouse gas (GHG) emissions of 1,3-BD production in the USA for different sources of ethanol, assuming that 1,3-BD is converted to SBR for automotive tires. The study was based on their Au/MgO/SiO2 catalyst, with an estimated 94% overall carbon selectivity by recycling acetaldehyde to the reactor in order to promote (eq 2). They concluded that the GHG footprint of ethanol largely determines the environmental sustainability of the process so that a low-carbon ethanol source is the key to achieving a reduction in GHG emissions related to petroleum-derived 1,3-BD. In addition, substantial reductions in GHG emissions can be achieved by locating the 1,3-BD plants close to oil refineries in order to export coproduced hydrogen and take advantage of the petrochemical infrastructure. Cespi et al.18 compared the cradle-to-gate life cycle assessment (LCA) of one-step and two-step processes, considering carbon footprint, cumulative energy demand (CED) and water consumption (WC) as environmental sustainability indicators. Inventory data for the LCA was extracted from a private report19 where catalysts by BASF20 and Daicel Corporation21 were evaluated for the one and two-step processes, respectively. For different sources of ethanol (USA, Brazil, Europe), the environmental sustainability indicators for the two-step process were worse than those of the one-step process due to the larger amount of ethanol used in the former, probably because unconverted ethanol was burnt rather than recovered and recycled to the rector. An aggregate sustainability score showed that the one-step process using ethanol from Brazil produces the most sustainable bio-butadiene. It is worth noting that in these studies, the catalyst performance was not modeled under industrial operating conditions, considering the presence of impurities in the ethanol feed, i.e. both recycled by-products and water in the ethanol feedstock, that can strongly affect product selectivity and ethanol conversion11,22. Since the reactor 7 performance dictates the design and performance of the plant, experimental data on catalyst performance under industrial conditions are necessary for an accurate TEA or LCA. In the previous studies by our research group on ethanol conversion to 1,3-BD, we selected a mixed Hf-Zn catalyst15 whose 1,3-BD carbon yield is one of the highest reported (~70%)2,23–26. The performance of this mixed Hf-Zn catalyst15 was experimentally studied under industrial operating conditions for the one-step process11,22. The results revealed that the combined effect of water and temperature on catalyst performance is significantly important: water promotes the formation of undesired ethanol dehydration products (ethylene and diethyl ether) but also inhibits the formation of heavy compounds, which is favored at a high reaction temperature. This indicates that water content in the ethanol which is fed to the reactor should be a process design variable. The aim of this work is to compare both the economic and environmental performance of a onestep process with the naphtha-cracking route for 1,3-BD production. The novelties of the work related to previous publications on 1,3-BD production from bioethanol are: (1) simulation of a one-step process using a reactor model built from data of a one-step catalyst performance under industrial operating conditions, which results in more accurate simulation of the industrial process; (2) Both TEA and LCA are performed on the same one-step process, so that its environmental and economic performance can be related, whereas in literature either TEA or LCA are only reported for different one-step processes; (3) The robustness of the LCA results of the one-step process are assessed by carrying out an uncertainty analysis. On the basis of the experimental Hf-Zn catalyst performance under industrial operating conditions11,22, a conceptual design of the one-step process was made and the resulting process, 8 which is described in the Material and Methods section, was simulated with Aspen Plus V8.827– 29. The TEA and LCA of the proposed one-step process using the Hf-Zn catalyst were carried out from the mass and energy balances from the simulation. Historical market prices for 1,3-BD produced from naphtha-cracking route were used as references for assessing the profitability of the one-step process. The 1,3-BD naphtha-based production process included in Ecoinvent (V3) database was chosen as a reference case for the environmental sustainability analysis. A sensitivity analysis was performed in the economic study to evaluate the effects of the uncertainty in capital investment and the market prices of ethanol and 1,3-BD on the profitability of the one-step process. In the environmental study, three different cases were defined to take into consideration the influence of the geographical location of the one-step process plant: Brazil, USA and Europe. For each scenario, an uncertainty analysis of the LCA results was performed. This article is part of a larger study which aims to assess the economic and environmental performance of both one and two-step processes for the conversion of ethanol to 1,3-BD using experimental data obtained by employing high-yield catalysts. Here, results for the one-step process are presented. The two-step process is under study and the results will be presented in a subsequent article along with a comparison with the one-step process. MATERIALS AND METHODS One-step process description and modeling Software Aspen Plus V8.8 was employed to model the one-step process route for 1,3-BD production from hydrous ethanol (93 wt% ethanol). The conceptual design of the process was made by following the hierarchical method proposed by Douglas30 and the Barnicki and Fair method for the separation train31,32. Here a brief and simplified description of the process is 9 provided based on the block diagram shown in Figure 1. A more detailed description along with the one-step process flowsheet simulated in Aspen Plus V8.8 can be found in Section S2 of the Supporting Information. Fresh ethanol is mixed with a recycle stream of purified ethanol, which contains some impurities (water and by-products), and the mixture is fed to a furnace reactor. The reactor effluent is cooled to separate the condensable fraction or crude recycled ethanol (unconverted ethanol, water, acetaldehyde, butanal, acetone, butanol and heavy compounds) from light gases (hydrogen, ethylene, propylene, butenes and 1,3-BD). Ethanol is used to absorb 1,3-BD from the light gases together with butenes and light polar compounds (Figure 1, Reaction and separation). Next, 1,3-BD is desorbed from ethanol, together with butenes and light polar compounds (mainly acetaldehyde), resulting in crude butadiene. Acetaldehyde is removed from crude butadiene by washing with water before extractive distillation with dimethylformamide (DMF) (Figure 1, Butadiene purification), by which butenes are separated from 1,3-BD, to produce polymer-grade 1,3-BD (99.9 wt% purity and acetaldehyde concentration lower than 10 ppm)33. On the other hand, the crude recycled ethanol is sent to a liquid-liquid extraction column (Figure 1, Removal of heavy compounds), where heavy compounds are extracted with an organic solvent (octane) so that the subsequent recovery of ethanol by distillation is not hindered by their presence33. Fresh water is also fed to the extraction column to enhance the recovery of ethanol. The extracted heavy compounds are used as fuel in the plant while the clean recycled ethanol is sent to a distillation train where water and other polar compounds are separated from ethanol (Figure 1, Separation of polar compounds). As a result of these separations, several streams are obtained: i) a purified recycled ethanol (7.5 wt% water), which is sent to the furnace reactor; ii) an acetaldehyde stream of high purity as co-product, which is partially recycled to the reactor; iii) a mixture of the rest of the separated polar compounds, which is used as fuel in the plant 16 Table 1. Catalyst performance input data for modelling the reactor and results of reactor model. Input data Model results Scenario B1 B2 B1 B2 Operating conditionsa Temperature (ºC) 380 360 380 360 Water in ethanol (wt%) 7.5 0 7.5 7.5 WHSVb (h-1) 1.12 0.64 1.12 0.64 Other impurities in ethanol (wt%) 0 0 11.3 2.9 Ethanol conversion (%) 96.5 98.8 81.9 87.1 Product carbon selectivity (%) Ethylene 8.70 10.00 9.85 14.62 Propylene 2.93 3.60 2.93 3.35 1-butene 2.70 2.50 2.70 2.07 1,3-BD 49.75 70.00 58.78 69.47 2-trans-butene 2.70 2.50 2.70 2.07 Acetaldehyde 11.59 2.40 8.13 4.08 Diethyl ether 1.30 1.40 1.29 2.64 Acetone 1.43 0.74 1.43 0.47 Butanol 0.23 0.06 0.23 0.07 Other polar compoundsc 10.26 6.80 3.55 1.17 Heavy compoundsd 8.40 0.00 8.40 0.00 a For input data, the operating conditions refer to those at which the catalytic test was performed. For model results, the operating conditions refer to those at which the reactor performance is estimated based on corrections of the input data; b Weight Hourly Space Velocity (h-1) is defined as the ratio: mass flow of ethanol compound (kg/h)/load of catalyst (kg); c the numerous other light organic polar compounds observed in the experiments are lumped into nbutanal; d heavy compounds are modeled as dodecane. 17 The overall mass and energy balances of B1 and B2 scenarios are compared in Table S5. The higher 1,3-BD selectivity (c.a.+10%) and per-pass ethanol conversion (c.a.+5%) of the Hf-Zn catalyst in the B2 scenario in comparison with the B1 scenario has important consequences on both the mass and energy performance of the process. First, the overall productivity of 1,3-BD is larger: 0.400 vs 0.334 tonne 1,3-BD/tonne anhydrous ethanol, or equivalently, lower raw ethanol (17%) is necessary per ton of 1,3-BD in the B2 scenario. The lower amount of raw ethanol to be processed and the lower generation of by-products, which facilitates their separation, result in lower consumption of utilities and solvents. For instance, the consumption of water, which is used to remove acetaldehyde from crude butadiene, and octane, which is used as solvent for the removal of heavy compounds, largely decreases due to lower selectivity to acetaldehyde and lower formation of heavy compounds, respectively. The lower water consumption leads to lower amounts of wastewater to be treated. On the other hand, the DMF required in the extractive distillation does not vary significantly since in both scenarios the ratio of butenes/1,3-BD is small. Regarding utilities, the lower generation of by-products is reflected in the lower heat loads of the re-boilers (steam) and condensers (CW) of the distillation columns to separate them from ethanol and 1,3-BD. In addition, the lower rate of ethanol to be processed reduces the consumption of natural gas in the furnace reactor, which also operates at a lower temperature. Overall, the total energy consumption (heating and cooling demand) of scenario B2 (25.5 GJ/tonne 1,3-BD) is 12% lower than that of scenario B1 (29.1 GJ/tonne 1,3-BD). In the literature lower total energy consumption has been reported for one-step processes: Cespi et al.18 reported 11.4 GJ/tonne 1,3-BD, Moncada et al.17 reported values between 8.8-14.3 GJ/tonne 1,3-BD and Shylesh et al.2 reported a total heating consumption of 6.2 GJ/tonne 1,3-BD. Apart from differences in process design, configuration and modeling, the main reason for lower energy 18 consumption in Cespi et al.18and Shylesh et al.2 is most likely the use of more efficient catalysts, and therefore, higher 1,3-BD overall productivity (0.511 and 0.550 tonne 1,3-BD/tonne ethanol, respectively). Certainly, the total energy consumption in our work and that of Cespi et al.18 and Shylesh et al.2 correlates very well (R2=0.96) with 1,3-BD overall productivity (tonne 1,3- BD/tonne ethanol), assuming that in the case of Shylesh et al.2 the ratio of heating consumption to cooling consumption is similar to ours. An exception is the work of Moncada et al.17 (0.279- 0.395 tonne 1,3-BD/tonne ethanol) who reported much lower energy consumption with 1,3-BD overall productivity. The reason might be that in their work the 1,3-BD plant was integrated within a bio-refinery, with a shared combined heat and power (CHP) system, and therefore, improved opportunities for heat integration. To summarize, the use of a more highly selective catalyst results in an important reduction in ethanol and energy consumption, which are critical aspects in the subsequent economic and environmental analysis. Economic assessment Figure 2 shows a breakdown of the MBSP for each scenario. The MBSP is largely determined by the operating costs (Table S6), mainly the cost of ethanol (86.8-92.7% of MBSP for B2 and B1 scenarios, respectively) and utilities. Since in the B2 scenario the consumption of ethanol and utilities is lower, the resulting MBSP is also smaller (1721 €/tonne against 1927 €/tonne). In the B1 scenario, the revenues from by-products are larger (Table S6) but they do not compensate the higher operating costs. In both scenarios, the contribution of the capital investment in the MBSP (depreciation and return on investment) is not substantial (7.4%-8.3% of MBSP for B2 and B1 scenarios, respectively) since the annualized CAPEX is relatively small compared to the 19 operating costs (Table S6). For the design capacity of 200 ktonne 1,3-BD/year, the specific CAPEX ranges from 0.9-1.1 M€/ktonne 1,3-BD. Figure 2. Breakdown of Minimum Butadiene Selling Price for each scenario. Figures over the bars indicate net MBSP, considering revenues from by-products. The process is close to being profitable since the MBSP of scenarios B1 and B2 is only 1.13-1.26 times higher than the mean market price of 1,3-BD in the last 10 years (1529 €/tonne), respectively. Because the 1,3-BD and ethanol market prices are highly volatile5, a sensitivity analysis was carried out where the price of azeotropic ethanol was changed within its upper and lower bounds in the last decade, and the resulting MBSP was compared with the 1,3-BD market price during the same period. In addition, the impact of the uncertainty in CAPEX estimation (± 30%) on the MBSP was assessed in the studied range of ethanol prices. The results of the sensitivity analysis are shown in Figure S2. The effect of the price of ethanol is substantial, as expected from the large share of ethanol costs in the MBSP. A change of 1 €/m3 in the ethanol price results in an increase of 3.3 and 4.1 €/tonne in the MBSP for the B2 and B1 scenario, respectively. The higher sensitivity in the B1 scenario was expected as a large amount of ethanol is necessary per tonne of 1,3-BD. On the other hand, the effect of uncertainty in CAPEX 1927 1721 -500 0 500 1000 1500 2000 2500 B1 B2 MBSP breakdown (€/tonne) Ethanol Fixed costs Depreciation Average income tax Average return on investment Other variable costs Revenues Total 20 estimation on MBSP is small, a change of ± 2.5 and ± 2.0% for B1 and B2 scenarios, respectively, since CAPEX has a relatively small influence on the MBSP, as mentioned before. By comparing the MBSP with the 1,3-BD market price for both scenarios it was determined that the probability of the process to be profitable for the B1 scenario is relatively low, because the MBSP is greater than the mean 1,3-BD market price for almost the whole interval of the ethanol price (Figure S2). For the B2 scenario the situation is more favorable, but if the 1,3-BD price plummets to its lowest value (~850 €/tonne) the process is unprofitable regardless of the price of ethanol. The market prices of ethanol and 1,3-BD seem to be unrelated 5, so it is difficult to predict the profitability of this route. As explained in the next section, this route could lead to a reduction in the GHG emissions compared to the fossil-based route. If the savings in GHG emissions were subsided, the economics of this route might improve so that the production of 1,3-BD from ethanol were more appealing. It is difficult to compare these economic results with those published so far in the literature by Moncada et al.17. The reason is that they evaluated 1,3-BD production from ethanol in the context of an integrated bio-refinery which previously produced ethanol from C6 sugars as raw material. Consequently, they reported the economic results of the whole line of production, from sugars to 1,3-BD. With that in mind, they calculated a MBSP between 3406-4369 €/tonne, much higher than the average 1,3-BD market price, concluding the 1,3-BD production from C6 sugars to be unprofitable. The MBSP was mainly determined by the cost of raw materials and the contribution of CAPEX to MBSP was marginal, which is similar to our results. They estimated a higher specific CAPEX, between 4-5.41 M€/ktonne 1,3-BD, because their production capacity was lower (24-34 ktonne 1,3-BD/year) and the investment of the entire line of production was considered. 21 Life cycle assessment This section compares the environmental impacts (GWP100, WC, CED) of 1,3-BD production under the two studied scenarios, B1 and B2, in three different locations, The United States (USA), Brazil (BR) and Europe (EU). At the same time, these six cases are compared with the production of 1,3-BD from the steam cracking of naphtha. The inventories for the LCA models are shown in Table S7. Regarding the robustness of the LCA, the authors found that the inventory items that most contributed to the impact categories were related to ethanol and therefore only uncertainty in the background inventory data of ethanol was considered. However, the uncertainty values (e.g. standard deviation) of these inventory items were missing in the Ecoinvent (V3) database. This was indirectly addressed by using impact values related to the production of each type of ethanol (crop and region) reported in the literature for each impact category. More information on the literature sources and calculation of uncertainty in the impact values can be found in section S4 of the Supporting Information. Next, the results for the GWP, WC and CED impact categories are presented and discussed. For each impact category, firstly, single-score results, obtained by using Ecoinvent (V3) background data, are analysed. Secondly, the robustness of the conclusions are assessed on the basis of the uncertainty study. Global Warming Potential Figure 3 depicts the single-score results obtained for the impact category GWP100 for each case. B2EU case is the best option in terms of GWP100 and, together with B1EU and B2USA cases, constitute the only three cases for which there is a reduction in this impact category with respect to the production of 1,3-BD from naphtha (8-26%). Ethanol production from biomass is largely 22 the main contributor to the GWP100 for all scenarios, ranging from 65-84% of the total impact. Hence, for the same location B2 cases have a lower impact (10-14%) when compared to B1 cases. In addition, the location of the plant largely affects the GWP100 values, increasing them by 11 and 116% when it is placed in USA and BR, respectively, rather than in the EU, mainly due to the different ethanol sources. In this sense, according to the results, both the ethanol source and the catalyst efficiency are determinant factors in carbon emissions. As can be seen in Figure 3, other important contributors to GWP100 are energy consumption (steam) (2-14%) and hydrogen peroxide used in the wastewater treatment (2-9%). On the other hand, the generation of co-products (hydrogen, ethylene, propylene, butenes and acetaldehyde) reduces the total impact due to the obtained credits for avoiding their production in other processes. The credits are coming mainly from end-of-life (56-68%), followed by hydrogen (15-23%) and ethylene (7- 10%). This indicates that the integration of the process with nearby facilities is important2. In addition, if the end-of-life practices are considered (see Life Cycle Assessment in Materials and Methods), GWP100 is reduced by 24-51% due to the resulting sequestration of biogenic carbon. All cases would show higher GWP100 than 1,3-BD from naphtha if carbon sequestration were not taken into account 2. 23 Figure 3. GWP100 considering the end-of-life of 1,3-BD as SBR. All background inventory data from Ecoinvent (V3) database. The dependence of the outcome on the selection of the background date source reveals itself when comparing these results with those from the uncertainty analysis (Figure 4). It is remarkable that the use of Brazilian ethanol results in a higher probability of lower GWP100 score than using USA corn-ethanol or the European ethanol mix, just the opposite than concluded with the single scores. The reason is that the GWP impact values predicted from Ecoinvent V3 database (Table S12) for Brazilian ethanol is overestimated compared with the median value found in literature (2570 against 570 kg CO2/tonne ethanol) because a very large contribution of the land use change impact is considered for Brazilian ethanol in the Ecoinvent55 V3 database (1975 kg CO2/tonne ethanol). Only for the B1BR and B2BR cases a reduction of emissions with respect to 1,3-BD from naphtha is very likely as the upper endpoint of the emission interval for those cases (2412 and 2025 kg CO2eq/tonne 1,3-BD, respectively) is lower than the reference emission of 1,3-BD from naphtha (2518 kg CO2eq/tonne 1,3-BD). Furthermore, net carbon sequestration is expected since the median of the GWP100 score is 2518 2247 1854 6351 5315 2770 2307 -4000 -2000 0 2000 4000 6000 8000 10000 BD from naphtha B1EU B2EU B1BR B2BR B1USA B2USA kg CO2eq/tonne 1,3-BD Others Steam Electricity H2O2 Ethanol Butadiene End of life Co-products Total 24 negative (-73 and -52 kg CO2eq/tonne 1,3-BD for B1BR and B2BR cases, respectively). Therefore, Brazil would be the best option for the location of the plant in terms of GWP100 impact. Between USA and Europe, it cannot be clearly concluded which location is better because the European ethanol-mix shows lower median GWP100 score, in line with what was observed with single scores, but the interval of possible GWP100 scores for European ethanol mix is wider. Figure 4. Uncertainty analysis of GWP100 using impact values of ethanol from literature. Median score for each case (kg CO2/tonne 1,3-BD): B1EU (3187); B1BR (-73); B1USA (3976); B2EU (2640); B2BR (-52); B2USA (3314). Water consumption Regarding water consumption, the bio-scenarios present single-score results much higher than the naphtha-derived process, mainly due to the water used in crop cultivation for ethanol production, which ranges from 94 to 98% of total WC (Figure 5). Obviously, the WC score is 25 lower (~18%) for the B2 scenario due to the lower consumption of ethanol with respect to B1. Under the same scenario, the WC scores for sugarcane (BR) and corn ethanol (USA) almost doubles that of the European mixed-crop ethanol (EU). The reason is the lower water consumption (m3/tonne ethanol) in the cultivation of sugar beet (20.8), rye (169) and wheat (114) of the EU mixed crop compared to USA corn (262) and Brazilian sugarcane (287), according to Ecoinvent V355 database (Table S13). Regarding the influence of the ethanol source, all these results on water consumption are in accordance, in qualitative terms, with those obtained by Cespi et al.18 but the absolute scores in our work are one order of magnitude larger. Figure 5. Water consumption score for each case. All background inventory data from Ecoinvent (V3) database. The uncertainty analysis shows a quite different picture (Figure 6). First, the median water consumption for the Brazilian and USA ethanol cases are lower than that of the European ethanol mix, just the opposite that from single scores. The reason is the difference in the water consumption impact values from Ecoinvent database and the median value from literature for each crop-based ethanol (Table S13). 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The environmental sustainability and economics of butadiene production from bioethanol is assessed using reaction data under industrial conditions. Economic assessment Minimum butadiene selling price Conceptual design and simulation Catalyst performance under industrial conditions LCA Influence of geographical location of plant