Microsoft Word - 8bove.docx CHEMICAL ENGINEERING TRANSACTIONS VOL. 50, 2016 A publication of The Italian Association of Chemical Engineering Online at www.aidic.it/cet Guest Editors: Katharina Kohse-Höinghaus, Eliseo Ranzi Copyright © 2016, AIDIC Servizi S.r.l., ISBN 978-88-95608-41-9; ISSN 2283-9216 Life Cycle Assessment of Technologies for Greenhouse Gas Emissions Reduction in Sugarcane Biorefineries Mateus F. Chagas a,b, Otávio Cavalett a, Bruno C. Klein a,b, Rubens Maciel Filhoa,b, Antonio Bonomi a,b a Laboratório Nacional de Ciência e Tecnologia do Bioetanol (CTBE), Centro Nacional de Pesquisa em Energia e Materiais (CNPEM), Caixa Postal 6192, CEP 13083-970, Campinas, São Paulo, Brasil b Faculdade de Engenharia Química (FEQ), Universidade Estadual de Campinas (Unicamp). CEP 13083-852, Campinas, São Paulo, Brasil. mateus.chagas@bioetanol.org.br Since sugarcane biorefineries are a large source of CO2 emissions, there is an opportunity of using or capturing this pollutant. An alternative would be to use mechanisms to capture, transport and inject CO2 into underground geological formations with the purpose of permanent storage of this gas, the so called Carbon Capture and Storage or CCS. Another possibility is to produce biodiesel from microalgae cultivated with CO2 to replace fossil diesel used in the sugarcane production chain. Environmental impacts using life cycle assessment of both technologies, CCS and biodiesel production from microalgae, integrated into first and second generation ethanol production plants were assessed. Biodiesel production from microalgae promoted reduction in all the assessed environmental impact categories, decreasing about 35 % of climate change impacts. CCS presented the highest climate change reduction transforming ethanol in a net carbon absorber. However, higher environmental impact in other categories are observed in this case. 1. Introduction One of the critical issues regarding biofuels production is the emissions of greenhouse gases (GHG) throughout their lifecycles. Despite the fact that ethanol produced from sugarcane in Brazil has been recognized as an advanced biofuel, it is necessary to search for technological alternatives to ensure even smaller life cycle GHG emissions. Since sugarcane processing plants present large CO2 emission (fermentation and combustion of biomass to attend plant power demand), there is a great potential for using or capturing this gas rather than releasing it into the atmosphere. An alternative to reduce GHG emissions associated with ethanol production process would be to use mechanisms to capture, transport and inject CO2 into underground geological formations with the purpose of permanent storage of this gas. Carbon Capture and Storage (CCS) applied to ethanol production plants may transform this process into a net carbon absorber, since CO2 emissions in the biorefinery largely exceed the amount of GHG emissions of ethanol production life cycle. Another possible alternative is to use the CO2 to increase the products portfolio of the sugarcane biorefinery by growing microalgae for the production of biodiesel (replacing fossil diesel in the agricultural and transport operations of sugarcane production stage) and coproducts. Even though there are no large-scale plants using these technologies, they are identified with great potential for reducing environmental impacts of biofuels. This study evaluates these two technological alternatives coupled to first and second generation sugarcane biorefineries, and their effects on the environmental impacts of ethanol. 2. Methods The Virtual Sugarcane Biorefinery (VSB) is a computer simulation platform developed by the Brazilian Bioethanol Science and Technology Laboratory (CTBE/CNPEM) (Bonomi et al., 2016). This tool was used to DOI: 10.3303/CET1650071 Please cite this article as: Chagas M., Cavalett O., Klein B., Maciel Filho R., Bonomi A., 2016, Life cycle assessment of technologies for greenhouse gas emissions reduction in sugarcane biorefineries, Chemical Engineering Transactions, 50, 421-426 DOI: 10.3303/CET1650071 421 evaluate the integration of both technologies, CCS and biodiesel production from microalgae, into first and second generation sugarcane biorefineries. Assessment of the agricultural stage of sugarcane production was carried out using the CanaSoft model (Bonomi et al., 2016). Sugarcane production system considers mechanized operations for planting, harvesting and recovery of 50% of the straw from the field using bales (Cardoso et al., 2013; Chagas et al., 2016). Aspen Plus® was used to simulate industrial processes, obtaining mass and energy balances for each evaluated scenario. Environmental impacts were assessed using Life Cycle Assessment methodology, aided by software SimaPro®. CML 2 Baseline 2000 v2.05 was selected as life cycle impact assessment method. Datasets for upstream processes are taken from ecoinvent 2.2 database, modified by Chagas et al. (2012). Environmental impacts are allocated between ethanol and coproducts based on the participation of each product on revenues (economic allocation). 2.1 Baseline scenarios for first and second generation An optimized first generation (1G) plant producing ethanol and surplus electricity (autonomous distillery), as described by Dias et al. (2014), was considered in this study. This plant produces ethanol from sugarcane juice (sucrose and reducing sugars) and operates only during the sugarcane harvesting period, which is around 200 days per year. Optimized features, such as straw recovery, reduced steam consumption, efficient high-pressure boilers and molecular sieves for ethanol dehydration process, allow large electricity surplus. This 1G process configuration is depicted in Figure 1. In the integrated 1G2G scenario, part of the lignocellulosic material (bagasse and straw) is sent to the 2G process. 2G process operates year-round (330 days) using lignocellulosic material stored during sugarcane season. The process starts with a steam explosion pretreatment followed by a separate hydrolysis and fermentation process. Pentoses (C5) liquor from pretreatment is fermented using a genetically modified microorganism, while glucose (C6) liquor from enzymatic hydrolysis is fermented along with 1G juice using conventional yeasts. Residual solids are burnt in the cogeneration unit. Process parameters for 2G process consider long term prospects as described by Milanez et al. (2015). A proposed block flow diagram for the 2G process integrated to the 1G autonomous distillery is presented in Figure 1. 2.2 Carbon Capture and Storage Only the highly concentrated CO₂ stream generated during ethanol fermentation was considered to be used for CCS, as presented in Figure 1. Using CO₂ also from cogeneration is also a possibility, but it would require additional downstream processes for purification and conditioning. In proposed CCS systems, CO₂ is transported from its source to a storage site through a pipeline and is then injected into the reservoir through an injection well, usually after compression. Parameters used to simulate this alternative integrated to 1G and 1G2G scenarios are presented in Table 1. Energy required to compress CO₂ for transportation and injection in the well were calculated using Aspen Plus®. This energy requirement as well as the material of the pipeline construction (carbon steel, 25 years lifespan) are considered in the life cycle inventories for the CCS scenarios. According to Goraieb et al. (2005), there are several geological formations in the state of São Paulo that could be used for CO₂ storage. An initial estimate for transportation distances between the biorefinery and injection wells was assumed as 200 km. A sensitivity analysis on the results considering 1000 km was also performed. Table 1: Summary of technical parameters for CCS scenarios Parameter Value Unit Reference Inlet pipeline pressure 9.6 MPa IPCC (2005) Injection pressure 15.0 MPa IPCC (2005), Goraieb et al (2005) Pipeline diameter (CCS coupled to 1G plant) 10 in Calculated based on CO₂ flow rates Pipeline diameter (CCS coupled to 1G2G plant) 14 in Calculated based on CO₂ flow rates Transport distance 200 km Goraieb et al (2005) 422 Sugarcane Reception and cleaning Extraction o f sugars Juice treatment and concentration Fermentatio n Distillati on Dehydration Juice An hydrous ethanol Bag asse Straw Combined heat and power g enerati on Pretreatment Enzymatic hyd rolysis Electricity Residual cellulignin C6 licor C5 licor Sugarcane production A g ri cu lt ur al st ag e In d us tr ia l s ta ge Al gae cultivatio n Harvesting and de-watering Oil extractio n Biodiesel production Biodiesel CO2 Vegetal impurities Ad justments and concentration C5 fermentation CO2 C5 wi ne Compression Pipeli ne transportati on Inj ection Geologic storage CO₂ CO₂ 2G alternative Al gae alternative CCS alternativ e T o r ep la ce d ie se l u se d in a gr ic ul tu ra l a nd t ra n sp or t op er at io ns Figure 1: Block flow diagram for integrated Algae and CCS scenarios in 1G and 1G2G biorefineries 2.3 Biodiesel production from microalgae scenarios Although high CO₂ purity is not required for algae culture, scenarios of biodiesel production from microalgae use only the CO₂ stream generated during ethanol fermentation in order to be compatible with CCS scenarios, as depicted in Figure 1. Several species of algae have been tested under different operational and environmental conditions. A wide variety of parameters for algae growing process is presented in literature, e.g. growth rate, oil content, ability to remove CO₂ from different sources and with different concentrations. A summary of main parameters used to simulate biodiesel production from algae is presented in Table 2. All the CO₂ from fermentation is considered to be used in the algae cultivation process. However, it would be necessary to store part of the CO2 to operate only during daylight period. A sensitivity analysis is presented considering that only 50% of CO₂ from fermentation is used for algae production and the other 50% is released to the atmosphere during the night. 423 For the biodiesel production from algae oil, an homogeneous alkaline transesterification using ethanol was considered. Part of the biodiesel produced by this scenario is used to replace the fossil diesel used in the agricultural operations of sugarcane production and transportation to the industrial plant. Biodiesel surplus is considered to be sold at the market as well as the other coproducts: algae meal and glycerine. Table 2: Summary of technical parameters for algae and biodiesel production scenarios Parameter Value Unit Reference Process parameters Algae productivity 25 g m−2 d−1 Quinn et al. (2014) Algae oil content 45.7 % Collet et al (2014) CO₂ required for algae 1.8 kgCO2 kgalgae−1 Olialgae (2015) CO₂ uptake 80.00 % Olialgae (2015) Extraction efficiency 85.5 % Quinn et al. (2014) Biodiesel conversion 98 % Cheng (2009) Inputs Urea 18 g kgalgae −1 Quinn et al. (2014) Diammonium phosphate 27 g kgalgae −1 Quinn et al. (2014) Coagulant 10 g kgalgae −1 Quinn et al. (2014) Hexane 5.3 g kgoil −1 Quinn et al. (2014) Ethanol 159 g kgbiodiesel −1 Del Vecchio (2006) Sodium hydroxide 0.8 g kgbiodiesel −1 Del Vecchio (2006) Hydrochloric acid 8.0 g kgbiodiesel −1 Del Vecchio (2006) Potassium hydroxide 5.5 g kgbiodiesel −1 Del Vecchio (2006) Energy consumption Algae cultivation 38 kWh ha−1 d−1 Quinn et al. (2014) Algae harvesting and oil extraction 0.018 kWh kgalgae −1 Quinn et al. (2014) Biodiesel production 25 kWh tbiodiesel −1 Del Vecchio (2006) 3. Results and discussion The key technical results for the evaluated scenarios are shown in Table 3. It can be noticed that integrated 1G2G process increases ethanol production by 46 %, but reduces electricity output by about 67 %. However, production of larger amount of liquid biofuel presents positive environmental results, as it can be seen in the comparative life cycle impacts presented in Table 4 and Figure 2. When integrating the 2G process into the biorefinery, the GHG emissions per unit of energy of ethanol are reduced by 20 %, with lower environmental impacts in all the evaluated categories. Table 3: Outputs in the biorefinery scenarios per metric tonne of processed sugarcane stalks Product Unit 1G 1G2G Base Algae CCS Base Algae CCS Anhydrous ethanol L 85.4 85.4 85.4 124.8 124.8 124.8 Electricity kWh 185.8 180.5 172.9 61.6 54.6 43.6 Biodiesel a L - 9.4 - - 15.3 - Glycerin (88%) kg - 1.3 - - 1.9 - Microalgae meal (37% protein) kg - 18.0 - - 26.4 - a Refers to the surplus biodiesel only; biodiesel used to replace fossil diesel in the agricultural operations is already accounted for. Biorefinery scenarios coupled with biodiesel production from algae slightly reduce surplus electricity due to energy requirements for microalgae cultivation, harvesting and oil extraction and conversion to biodiesel. This 424 reduction is more evident in 1G2G integrated scenarios, due to the large amount of CO₂ used in the process, since more ethanol is produced by C6 and C5 fermentation. Reduction in climate change impacts of ethanol production reaches 35 % for both 1G algae and 1G2G algae scenarios when compared to respective Baseline scenarios. This reduction is mainly due to fossil diesel replacement in the sugarcane production phase. Even higher reduction is observed in the abiotic depletion, since fossil oil used for diesel production has an important contribution in this environmental impact. Lower reduction observed in other assessed categories are due to nutrients used for microalgae cultivation. A sensitivity analysis considering that only 50% of CO₂ from fermentation is used obviously leads to a lower reduction in GHG emissions. About 30% lower climate change impacts for both 1G algae and 1G2G algae scenarios compared to respective Baseline scenarios. CCS scenarios show the best results for climate change impacts. Biorefineries with CCS have the ability to make ethanol production process a net carbon absorber since the captured and stored CO2 largely exceeds the GHG emitted from the entire ethanol production life cycle. Applying this technology, emissions fall from 20 to -8.8 g CO₂ eq per MJ of ethanol in 1G process, and from 16.1 to -17.5 g CO₂ eq per MJ of ethanol in integrated 1G2G process. These reductions could be even higher if CO₂ from flue gases is included in the analysis. Reduction in surplus electricity and pipeline construction inputs slightly increases ethanol impacts in all the other considered environmental impact categories, as shown in Figure 2. A sensitivity analysis considering longer distances (1000 km) for CO₂ transportation with recompression units every 200 km shows that CCS coupled with 1G would result in climate change impacts of -7.8 g CO₂ eq/MJ, and, coupled with 1G2G, to -17.0 g CO₂ eq/MJ. It indicates that even for large transport distances CCS could present very interesting results in terms of climate change impacts. Table 4: Greenhouse gas emissions for ethanol produced in the evaluated scenarios (g CO₂ eq/MJethanol) Life cycle emissions 1G 1G2G Base Algae CCS Base Algae CCS Sugarcane and straw production 16.8 10.0 17.0 13.4 7.6 13.6 Process emissions 2.3 1.9 2.3 1.1 0.8 1.1 1G and 2G inputs 0.9 0.7 0.9 1.6 1.1 1.6 Microalgae and biodiesel inputs - 0.9 - - 1.0 - CCS infrastructure - - 0.2 - - 0.1 CO₂ captured and stored - - -29.2 - - -33.9 Final score 20.0 13.5 -8.8 16.1 10.5 -17.2 Figure 2: Relative environmental impacts for evaluated scenarios 425 4. Conclusions Both technologies – CCS and biodiesel production from microalgae – integrated into 1G and 1G2G ethanol autonomous plants were assessed in this study. Biodiesel production from microalgae promoted reductions in all the assessed environmental impact categories, decreasing greenhouse gases (GHG) emissions in about 35 % when compared to baseline scenarios. CCS presented the highest potential of reducing GHG emissions, transforming the ethanol production process into a net carbon absorber. However, negative consequences in other environmental impact categories are observed. Despite the promising environmental performance, these technologies have to prove to be economically sustainable to be applied in large scale. Further economic analysis will help to better understanding sustainability of these biorefinery scenarios. Acknowledgments The authors would like to thank Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP (contract grant number 2010/17139-3) for financial support. Reference Bonomi A., Cavalett O., Cunha M.P, Lima, M.A.P., 2016, Virtual Biorefinery: An Optimization Strategy for Renewable Carbon Valorization. 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