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Blade manufacturing for onshore and offshore wind farms: the energy and environmental performance for a case study in Brazil

Manufatura de pás para parques eólicos onshore e offshore: o desempenho energético e ambiental para um estudo de caso no Brasil

Abstract

This study aims to analyze the energy and environmental performance of the manufacture of two models of wind turbine blades for a 300 MW wind farm. Material flow analysis (MFA) was used to prepare the mass balance, while life cycle assessment (LCA), based on ISO-14044, was used to evaluate three impact categories, considering sensitivity analysis to evaluate the replacement of wind turbine blade materials. Results showed that the manufacturing of wind turbine blades causes a 10% loss of material impregnated with fiberglass and epoxy resin. Fiberglass was the input with the highest contribution to water consumption, energy consumption, and the carbon footprint. The sensitivity analysis showed that, for the offshore scenario of higher capacity factor and longer lifetime, the carbon footprint contribution per electricity to be produced was 0.214 kg CO2eq/GJ, while for the onshore scenario of lower capacity factor and shorter lifetime, it was 1.37 kg CO2eq/GJ. When using jute fiber grown without irrigation as a substitute input for fiberglass, the reduction was 38% (onshore) and 42% (offshore) in water consumption, 18% (onshore and offshore) in energy consumption, and 24% (onshore) and 25% (offshore) in carbon footprint. The onshore model had a larger impact in all the categories evaluated than the offshore model. Therefore, the use of unirrigated jute fiber allows gains in energy and environmental performance.

Keywords:
Renewable energy; Wind energy; Life cycle assessment; Environmental performance; Wind turbine blades; Composite material

Resumo

Este estudo tem como objetivo analisar o desempenho energético e ambiental da manufatura de dois modelos de pás de turbina eólica para compor um parque eólico de 300 MW. A Análise de Fluxo de Material (AFM) foi utilizada para elaborar o balanço de massa, enquanto a Avaliação do Ciclo de Vida (ACV) baseada na NBR ISO-14044 foi utilizada para avaliar três categorias de impacto, na qual a análise de sensibilidade foi considerada para avaliar a substituição de materiais da pá de turbina eólica. Os resultados indicaram que a manufatura das pás de turbina eólica gera uma perda de 10% de material impregnado com fibra de vidro e resina epóxi. A fibra de vidro foi o insumo que apresentou a maior contribuição em relação ao consumo de água, consumo de energia e pegada de carbono. A análise de sensibilidade evidenciou que, para o cenário offshore de maior fator de capacidade e maior vida útil, a contribuição da pegada de carbono por eletricidade a ser produzida foi 0,214 kg CO2eq/GJ, enquanto para o cenário de onshore de menor fator de capacidade e menor vida útil foi 1,37 kg CO2eq/GJ. Ao se utilizar a fibra vegetal de juta cultivada sem irrigação como um insumo substituto da fibra de vidro, a redução do consumo de água é de 38% (onshore) e 42% (offshore), do consumo de energia é de 18% (onshore e offshore) e da pegada de carbono é de 24% (onshore) e 25% (offshore). O modelo onshore apresentou um maior impacto que o offshore em todas as categorias avaliadas. Portanto, é possível obter ganhos no desempenho energético e ambiental empregando fibra vegetal de juta não irrigada.

Palavras-chave:
Energia renovável; Energia eólica; Avaliação do ciclo de vida; Desempenho ambiental; Pá de turbina eólica; Material compósito

1 Introduction

In 2019, 27% of the world’s electricity came from renewable sources, while 73% came from non-renewable sources (IEA, 2022International Energy Agency – IEA. (2022). Electricity production – electricity information: overview – analysis. Retrieved in 2023, March 21, from https://www.iea.org/reports/electricity-information-overview/electricity-production
https://www.iea.org/reports/electricity-...
). Coal, oil, and natural gas are used as fuel in the traditional energy production system. These materials have many hydrocarbons, which, when burned, release CO2 and other greenhouse gases. According to Mello et al. (2020)Mello, G., Dias, M. F., & Robaina, M. (2020). Wind farms life cycle assessment review: CO2 emissions and climate change. Energy Reports, 6, 214-219. http://dx.doi.org/10.1016/j.egyr.2020.11.104.
http://dx.doi.org/10.1016/j.egyr.2020.11...
, who used life cycle assessment (LCA) to compare energy production cycles, as wind energy produces less emissions and environmental impacts during the operation phase than fossil fuel energy, it is considered a “cleaner” generation source.

With an average annual growth rate of 13% for installed capacity from 2011 to 2021, wind energy is one of the fastest growing sources of power generation in the world (Cooperman et al., 2021Cooperman, A., Eberle, A., & Lantz, E. (2021). Wind turbine blade material in the United States: quantities, costs, and end-of-life options. Resources, Conservation and Recycling, 168, 105439. http://dx.doi.org/10.1016/j.resconrec.2021.105439.
http://dx.doi.org/10.1016/j.resconrec.20...
; GWEC, 2022Global Wind Energy Council – GWEC. (2022). Global wind report 2022. Brussels: Global Wind Energy Council. Retrieved in 2023, March 21, from https://gwec.net/wp-content/uploads/2022/04/Annual-Wind-Report-2022_screen_final_April.pdf
https://gwec.net/wp-content/uploads/2022...
). The number of wind farms installed in Brazil has increased significantly in recent years. According to ABEEÓLICA (2022)Associação Brasileira de Energia Eólica – ABEEÓLICA. (2022). Boletim anual de geração eólica 2021. Retrieved in 2023, March 21, from https://abeeolica.org.br/energia-eolica/dados-abeeolica/?ano=2022
https://abeeolica.org.br/energia-eolica/...
, this capacity expanded from 1 524 MW in 2011 to 21 577 MW in 2021, which implies an average growth rate of 30% per year. Moreover, according to ABEEÓLICA (2022)Associação Brasileira de Energia Eólica – ABEEÓLICA. (2022). Boletim anual de geração eólica 2021. Retrieved in 2023, March 21, from https://abeeolica.org.br/energia-eolica/dados-abeeolica/?ano=2022
https://abeeolica.org.br/energia-eolica/...
, Northeastern Brazil, which includes the states of Rio Grande do Norte, Bahia, Piauí, and Ceará, accounted for 88.7% of all wind energy produced in Brazil in 2021.

The basic parts of a wind turbine are the foundation, tower, blades, rotor, hub, shaft, nacelle, and generator (ABDI, 2017Agência Brasileira de Desenvolvimento Industrial – ABDI. (2017). Atualização do mapeamento da cadeia produtiva da indústria eólica no Brasil. Brasília: Agência Brasileira de Desenvolvimento Industrial. Retrieved in 2023, March 21, from https://docplayer.com.br/109774745-Atualizacao-do-mapeamento-da-cadeia-produtiva-da-industria-eolica-no-brasil.html
https://docplayer.com.br/109774745-Atual...
). More powerful wind turbines and larger-scale wind farms are needed to harness more wind energy and lower the cost of electricity generation. Structural components must meet design requirements for stiffness, mechanical and fatigue strength, environmental durability, light weight, low cost, and the availability of end-of-life recycling solutions (Müssig et al., 2020Müssig, J., Amaducci, S., Bourmaud, A., Beaugrand, J., & Shah, D. U. (2020). Transdisciplinary top-down review of hemp fibre composites: from an advanced product design to crop variety selection. Composites Part C: Open Access, 2, 100010. http://dx.doi.org/10.1016/j.jcomc.2020.100010.
http://dx.doi.org/10.1016/j.jcomc.2020.1...
). For both onshore and offshore models, the energy production and lifetime of wind turbines significantly affect the intensity of greenhouse gas emissions (Wang et al., 2019aWang, S., Wang, S., & Liu, J. (2019a). Life-cycle green-house gas emissions of onshore and offshore wind turbines. Journal of Cleaner Production, 210, 804-810. http://dx.doi.org/10.1016/j.jclepro.2018.11.031.
http://dx.doi.org/10.1016/j.jclepro.2018...
).

In the case of wind farms, the most significant environmental impact concerns the major components, such as towers, foundations, and blades, which consume the most electricity during manufacture, resulting in indirect emissions. The installation and operation stages contribute little to emissions (Chipindula et al., 2018Chipindula, J., Botlaguduru, V., Du, H., Kommalapati, R., & Huque, Z. (2018). Life cycle environmental impact of onshore and offshore wind farms in Texas. Sustainability, 10(6), 2022. http://dx.doi.org/10.3390/su10062022.
http://dx.doi.org/10.3390/su10062022...
). Gomaa et al. (2019)Gomaa, M. R., Rezk, H., Mustafa, R. J., & Al-Dhaifallah, M. (2019). Evaluating the environmental impacts and energy performance of a wind farm system utilizing the life-cycle assessment method: a practical case study. Energies, 12(17), 3263. http://dx.doi.org/10.3390/en12173263.
http://dx.doi.org/10.3390/en12173263...
found that the manufacturing stage accounted for the greatest impact, 91% of global warming and 64% of cumulative energy demand, when evaluating wind farms using the LCA method. The manufacturing stage contributes almost 90% of the total emissions of the entire wind farm life cycle (Mello et al., 2020Mello, G., Dias, M. F., & Robaina, M. (2020). Wind farms life cycle assessment review: CO2 emissions and climate change. Energy Reports, 6, 214-219. http://dx.doi.org/10.1016/j.egyr.2020.11.104.
http://dx.doi.org/10.1016/j.egyr.2020.11...
). Regarding wind turbine blades, the production of the materials - mainly fiberglass and epoxy resin - represents their largest contribution to greenhouse gas emissions (Chiesura et al., 2020Chiesura, G., Stecher, H., & Jensen, J. P. (2020). Blade materials selection influence on sustainability: a case study through LCA. IOP Conference Series. Materials Science and Engineering, 942(1), 012011. http://dx.doi.org/10.1088/1757-899X/942/1/012011.
http://dx.doi.org/10.1088/1757-899X/942/...
).

Except for wind turbine blades, which are composites and often have a high proportion (60–70%) of fiber reinforced polymer (FRP) or carbon fiber reinforced polymer (CFRP), most wind turbine components are recycled (Deeney et al., 2021Deeney, P., Nagle, A. J., Gough, F., Lemmertz, H., Delaney, E. L., McKinley, J. M., Graham, C., Leahy, P. G., Dunphy, N. P., & Mullally, G. (2021). End-of-life alternatives for wind turbine blades: sustainability Indices based on the UN sustainable development goals. Resources, Conservation and Recycling, 171, 105642. http://dx.doi.org/10.1016/j.resconrec.2021.105642.
http://dx.doi.org/10.1016/j.resconrec.20...
; Jensen & Skelton, 2018Jensen, J. P., & Skelton, K. (2018). Wind turbine blade recycling: experiences, challenges and possibilities in a circular economy. Renewable & Sustainable Energy Reviews, 97, 165-176. http://dx.doi.org/10.1016/j.rser.2018.08.041.
http://dx.doi.org/10.1016/j.rser.2018.08...
). Thus, their final destination is a major source of environmental concern (EPE, 2021Empresa de Pesquisa Energética – EPE. (2021). Empreendimentos eólicos ao fim da vida útil – situação atual e perspectivas futuras. Brasília: Empresa de Pesquisa Energética. Retrieved in 2023, March 21, from https://www.epe.gov.br/sites-pt/publicacoes-dados-abertos/publicacoes/PublicacoesArquivos/publicacao-563/NT-EPE-DEE-012-2021.pdf
https://www.epe.gov.br/sites-pt/publicac...
). The recycling of thermoset FRP blades from mechanical and thermochemical processes has received more attention as a result of the increasing number of wind turbine blades reaching the end of their lifetime and concerns about resource conservation and environmental protection (Dorigato, 2021Dorigato, A. (2021). Recycling of thermosetting composites for wind blade application. Advanced Industrial and Engineering Polymer Research, 4(2), 116-132. http://dx.doi.org/10.1016/j.aiepr.2021.02.002.
http://dx.doi.org/10.1016/j.aiepr.2021.0...
).

However, after reaching the end of their lifetime, wind turbine blades are often disposed in landfills or burned (Ramos & Almeida, 2021Ramos, M. J. Jr., & Almeida, E. S. (2021). Destinação de pás de turbinas eólicas instaladas no estado da Bahia, Brasil. Revista Brasileira de Gestão Ambiental e Sustentabilidade, 8(19), 979-992. http://dx.doi.org/10.21438/rbgas(2021)081924.
http://dx.doi.org/10.21438/rbgas(2021)08...
). The National Solid Waste Policy guidelines (Brasil, 2010Brasil. Presidência da República. (2010, August 3). Lei nº 12.305, de 2 de agosto de 2010. Institui a Política Nacional de Resíduos Sólidos; altera a Lei nº 9.605, de 12 de fevereiro de 1998; e dá outras providências (seção 1, p. 3). Brasília, DF: Diário Oficial da República Federativa do Brasil. Retrieved in 2023, March 21, from http://www.planalto.gov.br/ccivil_03/_ato2007-2010/2010/lei/l12305.htm
http://www.planalto.gov.br/ccivil_03/_at...
) and the list of waste management priorities required to create a circular economy, which follows the model of Directive 2008/98/EC of the European Parliament and the European Council (European Union, 2008European Union. (2008). Directive 2008/98/EC of the European Parliament and of the Council, November 19, 2008, on waste and repealing certain directives. Brussels: European Union. Retrieved in 2023, March 21, from http://data.europa.eu/eli/dir/2008/98/oj/eng
http://data.europa.eu/eli/dir/2008/98/oj...
), place these two solutions at the bottom levels of the hierarchy. The aforementioned studies showed that the growth of the wind industry and the alternatives for disposal after use led to an increase in composite materials use. However, no actions were suggested to decrease the sources that generate waste or affect the energy and environmental performance of the inputs used in wind energy.

Thus, this study aims to analyze the energy and environmental performance of the manufacture of two models of wind turbine blades (onshore and offshore). We used material flow analysis (MFA) to prepare the mass balance, LCA to evaluate energy and environmental performance, and sensitivity analysis to evaluate the replacement of wind turbine blade materials.

2 Methodology

This study evaluated wind turbine blades for onshore and offshore wind farms, made of composite material and manufactured in the Pecém Industrial and Port Complex (CIPP – Complexo Industrial e Portuário do Pecém) in Caucaia, Ceará, Brazil. MFA (Brunner & Rechberger, 2003Brunner, P. H., & Rechberger, H. (2003). Practical handbook of material flow analysis. Boca Raton: CRC Press. http://dx.doi.org/10.1201/9780203507209.
http://dx.doi.org/10.1201/9780203507209...
) and LCA, based on ISO-14044 (ABNT, 2009Associação Brasileira de Normas Técnicas – ABNT. (2009). NBR ISO 14044: gestão ambiental—avaliação do ciclo de vida—requisitos e orientações. São Paulo: Associação Brasileira de Normas Técnicas.), were the methods used. The annual output of the factory was considered sufficient to supply a wind farm with a nominal capacity of 300 MW (on-demand manufacturing). Two wind turbine blade models (onshore and offshore) were analyzed. The purpose of wind turbine blades is to collect the kinetic energy of the wind, which is then transformed into mechanical energy.

The production of wind turbine blades for a wind farm with a nominal capacity of 300 MW is the functional unit considered in this study. Since each wind turbine in the onshore model has a rated output power of 4 MW, this model requires 75 wind turbines and 225 wind turbine blades. The Chinese company MingYang Defeng Energy Systems CO.LTD is the manufacturer of the MySE4.0-145 wind turbine. The rotor has a diameter of 145 m, a surface area of 16 505 m2, a nominal weight of 19.7 t, and three blades (Bauer & Matysik, 2022Bauer, L., & Matysik, S. (2022). Windturbines database. Retrieved in 2023, March 21, from https://en.wind-turbine-models.com/turbines
https://en.wind-turbine-models.com/turbi...
).

The offshore model required 25 wind turbines and 75 wind turbine blades, since each wind turbine has a rated output power of 12 MW. General Electric (GE) Renewable Energy manufactures the Haliade-X wind turbine in Germany. The rotor has a diameter of 220 m, a surface area of 38,000 m2, a nominal weight of 55 t, and three blades (Bauer & Matysik, 2022Bauer, L., & Matysik, S. (2022). Windturbines database. Retrieved in 2023, March 21, from https://en.wind-turbine-models.com/turbines
https://en.wind-turbine-models.com/turbi...
).

The STAN program version 2.7.101 was used to complete MFA, which was initiated for the onshore model by Ramos et al. (2022)Ramos, M. J. Jr., Medeiros, D. L., & Almeida, E. S. (2022). Wind turbine blade manufacturing: a material flow analysis. In VIII International Symposium on Innovation and Technology (pp. 288-296). Camaçari: SENAI CIMATEC. https://doi.org/10.5151/siintec2022-245225.
https://doi.org/10.5151/siintec2022-2452...
and complemented for the offshore model in this study. According to the Austrian standard ÖNORM S 2096 (Material flow analysis – Part 1: Application in waste management), STAN (short for subSTance flow ANalysis) is a free software used for MFA (TUV, 2022Technische Universität Wien – TUV. (2022). About STAN. Retrieved in 2023, March 21, from https://www.stan2web.net/
https://www.stan2web.net/...
). Figure 1 shows the product system evaluated in this study.

Figure 1
Product system: manufacture of wind turbine blades. The flows are classified as import (I) or export (E).

2.1 Transportation inventory

In total, 225 wind turbine blades were manufactured for the onshore model and 75 for the offshore model. Table 1 presents the quantities of material (Q, in t) and the distance (d, in km) over which they were transported from the suppliers’ exit gates to the manufacturer’s entrance gates in Ceará. The Brazilian Agency for Industrial Development provided information about the location of the main suppliers of the raw materials used to manufacture the Brazilian wind turbine blades (ABDI, 2017Agência Brasileira de Desenvolvimento Industrial – ABDI. (2017). Atualização do mapeamento da cadeia produtiva da indústria eólica no Brasil. Brasília: Agência Brasileira de Desenvolvimento Industrial. Retrieved in 2023, March 21, from https://docplayer.com.br/109774745-Atualizacao-do-mapeamento-da-cadeia-produtiva-da-industria-eolica-no-brasil.html
https://docplayer.com.br/109774745-Atual...
).

Table 1
Supplier transportation inventory for the manufacture of wind turbine blades.

For each model, the transportation cargo was estimated by multiplying the quantity of material by the distance traveled. For road transport, the distance value was doubled, considering that each supplier’s fleet would handle the delivery and each truck would pick up the input at the port or at the wind turbine blades manufacturer before returning to its base. According to National Transit Council Resolution No. 882, it was determined that each vehicle is a semi-trailer truck measuring 2.60 m wide, 4.40 m high, and 14 m long, with 23 t total gross weight and a payload capacity of 14 t (Brasil, 2021Brasil. Conselho Nacional de Trânsito – CONTRAN. (2021, December 24). Resolução CONTRAN nº 882, de 13 de dezembro de 2021. Estabelece os limites de pesos e dimensões para veículos que transitem por vias terrestres, referenda a Deliberação CONTRAN nº 246, de 25 de novembro de 2021, e dá outras providências (seção 1, nº 242, p. 153). Brasília, DF: Diário Oficial da República Federativa do Brasil. Retrieved in 2023, March 21, from https://www.in.gov.br/en/web/dou/-/resolucao-contran-n-882-de-13-de-dezembro-de-2021-370017699
https://www.in.gov.br/en/web/dou/-/resol...
). For transportation by ship, a short distance was considered since the ship would make more trips before returning to port of origin.

This study assumed that national inputs would be transported by the Brazilian highway system and imported inputs, after being transported by truck to the nearest port, would be shipped to the Port of Santos followed by the highway road network to the manufacturer of the wind blades.

2.2 Energy and environmental performance

The structure of the wind turbine blades evaluated in this study included fiberglass fabric, epoxy resin, metal fasteners and nuts, adhesives, balsa wood, protective coating (paint), and polyurethane foam (ABDI, 2017Agência Brasileira de Desenvolvimento Industrial – ABDI. (2017). Atualização do mapeamento da cadeia produtiva da indústria eólica no Brasil. Brasília: Agência Brasileira de Desenvolvimento Industrial. Retrieved in 2023, March 21, from https://docplayer.com.br/109774745-Atualizacao-do-mapeamento-da-cadeia-produtiva-da-industria-eolica-no-brasil.html
https://docplayer.com.br/109774745-Atual...
). Liu & Barlow (2016)Liu, P., & Barlow, C. Y. (2016). The environmental impact of wind turbine blades. IOP Conference Series. Materials Science and Engineering, 139, 012032. http://dx.doi.org/10.1088/1757-899X/139/1/012032.
http://dx.doi.org/10.1088/1757-899X/139/...
estimated the percentage of material by weight of a wind turbine blade (Table 2). According to Giannetti et al. (2012)Giannetti, B. F., Bonilla, S. H., & Almeida, C. M. V. B. (2012). Cleaner production initiatives and challenges for a sustainable world. Journal of Cleaner Production, 22(1), I. http://dx.doi.org/10.1016/S0959-6526(11)00431-8.
http://dx.doi.org/10.1016/S0959-6526(11)...
, during the production process, the epoxy resin impregnates the fiberglass in a liquid state, which, as a result of a curing reaction, transforms into a solid state over time. Information provided by the manufacturers pointed that the total mass of each wind turbine blade was 20 t in the onshore model and 55 t in the offshore model (Bauer & Matysik, 2022Bauer, L., & Matysik, S. (2022). Windturbines database. Retrieved in 2023, March 21, from https://en.wind-turbine-models.com/turbines
https://en.wind-turbine-models.com/turbi...
). In line with the national manufacturer of wind turbine blades, the energy consumption of the onshore and offshore models per blade produced was 87 GJ (Aeris Energy, 2022Aeris Energy. (2022). Relatório de sustentabilidade 2021. Caucaia: Aeris Energy. Retrieved in 2023, March 21, from https://www.aerisenergy.com.br/sites/default/files/nosso-proposito-sustentabilidade/arquivos/relatorio_sustentabilidade_aeris_2021_V2.pdf
https://www.aerisenergy.com.br/sites/def...
).

Table 2
Foreground inventory of the manufacturing of a blade for onshore and offshore wind farms.

Liquefied petroleum gas (LPG) is used in the forklifts, while diesel fuel is used in cranes, forklifts, and semi-trailer trucks that lift and move cargo. Electricity powers the machinery used to cut fiberglass fabrics, inject epoxy resin, run vacuum pumps to remove air from infusions, deburr surfaces, fix flaws (using hand tools such as sanders and drills), and apply the finishing touches (sanders and electric compressor for painting). Gasoline and ethanol are used in the vehicles that transport workers.

Table 2 presents the mass contribution of the materials used and the production inventory of one unit for each wind turbine blade included in this study. Appendix 1 Appendix 1 The basic uncertainty and pedigree score. Table A1 Basic uncertainty and pedigree score of inventory flows. Material Basic uncertainty in GSD2* Pedigree score [Pedigree uncertainty in GSD2] a Name in openLCA® 1.11.0 Input Fiberglass fabric b 1.05 4,2,2,1,3 glass fibre reinforced plastic production, polyamide, injection moulded | glass fibre reinforced plastic, polyamide, injection moulded | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Epoxy resin 1.05 4,2,2,1,3 epoxy resin production | epoxy resin | Cutoff, U – RoW [1.20;1.02;1.03;1.00;1.20] Metal fasteners and nuts 1.05 4,2,2,1,3 steel production, chromium steel 18/8, hot rolled | steel, chromium steel 18 [1.20;1.02;1.03;1.00;1.20] Adhesives 1.05 4,2,2,1,3 bitumen adhesive compound production, hot | bitumen adhesive compound, hot | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Balsa wood 1.05 4,2,2,1,3 beam, hardwood, raw, kiln drying to u=10% | sawnwood, beam, hardwood, raw, dried (u=10%) | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Polyurethane foam 1.05 4,2,2,1,3 polyurethane production, flexible foam | polyurethane, flexible foam | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Protective coating (paint) 1.05 4,2,2,1,3 coating powder production | coating powder | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Energy, diesel 1.05 1,4,1,1,1 market for diesel, burned in agricultural machinery | diesel, burned in agricultural machinery | Cutoff, U - GLO [1.00; 1.10; 1.00; 1.00; 1.00] Energy, gasoline 1.05 1,4,1,1,1 market for petrol, unleaded, burned in machinery | petrol, unleaded, burned in machinery | Cutoff, U - GLO [1.00; 1.10; 1.00; 1.00; 1.00] Energy, LPG 1.05 1,4,1,1,1 heat production, propane, at industrial furnace >100kW | heat, district or industrial, other than natural gas | Cutoff, U - RoW [1.00; 1.10; 1.00; 1.00; 1.00] Energy, ethanol c 1.05 1,4,1,1,1 ethanol production from sugarcane | ethanol, without water, in 95% solution state, from fermentation | Cutoff, U – BR; treatment of bagasse, from sugarcane, in heat and power co-generation unit, 6400kW thermal | heat, district or industrial, other than natural gas | Cutoff, U – GLO (without the fuel bagasse, from sugarcane) [1.00; 1.10; 1.00; 1.00; 1.00] Energy, electricity 1.05 1,4,1,1,1 market for electricity, low voltage | electricity, low voltage | Cutoff, U - BR [1.00; 1.10; 1.00; 1.00; 1.00] Transportation, truck 2.00 3,4,1,5,2 market for transport, freight, lorry, unspecified | transport, freight, lorry, unspecified | Cutoff, U - GLO [1.10;1.10;1.00;1.10;1.05] Transportation, ship 2.00 3,4,1,5,2 market for transport, freight, sea, transoceanic ship | transport, freight, sea, transoceanic ship | Cutoff, U - GLO [1.10;1.10;1.00;1.10;1.05] Output Losses (fiberglass and epoxy-impregnated material) 1.05 4,3,3,1,2 market for inert waste, for final disposal | inert waste, for final disposal | Cutoff, U - RoW [1.20;1.05;1.10;1.00;1.05] RoW: Rest of World. GLO: Global. *GSD2: relative squared geometric standard deviation. aPedigree matrix indicators: source reliability, completeness, temporal correlation, geographic correlation, and technology correlation, respectively. The inventory database was used (ecoinvent_case_studies_Ceramic_cup_vs_Paper_cup) with a method database (openLCA_LCIA_pack_2_1_3). bTextile production, jute | textile, jute | Cutoff, U – RoW was considered in the sensitivity analysis of the replacement of fiberglass by jute fiber grown without irrigation. cFor ethanol, the combination of two supplier inventories was considered: one representing the production of 0.0007 t of the fuel and the other representing the burning of 0.02 GJ of the fuel per blade. Equation A1 (Rosenbaum et al., 2018) combined the basic uncertainty and the pedigree uncertainties of each inventory flow: G S D X 2 : = e ∑ i = 1 n l n G S D X i 2 2 (A1) Equation A2 converted GSD2, representing a 95.45% confidence interval, into GSD, representing a 68% confidence interval: G S D X : = G S D X 2 (A2) Equation A3 (Ciroth et al., 2012) converted the combined uncertainty of each inventory flow into relative arithmetic standard deviation, or coefficient of variation (CV): C V X : = e l n G S D X 2 - 1 (A3) (Table A1) shows that the basic uncertainty and the pedigree score (Weidema et al., 2013Weidema, B. P., Bauer, C., Hischier, R., Mutel, C., Nemecek, T., Reinhard, J., Vadenbo, C. O., & Wernet, G. (2013). Overview and methodology (data quality guideline for the Ecoinvent Database version 3. Ecoinvent report 1(v3). St. Gallen: The Ecoinvent Centre/Swiss Centre for Life Cycle Inventories.) were used to estimate the relative arithmetic standard deviation of the quantities.

The background inventory (Appendix 1 Appendix 1 The basic uncertainty and pedigree score. Table A1 Basic uncertainty and pedigree score of inventory flows. Material Basic uncertainty in GSD2* Pedigree score [Pedigree uncertainty in GSD2] a Name in openLCA® 1.11.0 Input Fiberglass fabric b 1.05 4,2,2,1,3 glass fibre reinforced plastic production, polyamide, injection moulded | glass fibre reinforced plastic, polyamide, injection moulded | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Epoxy resin 1.05 4,2,2,1,3 epoxy resin production | epoxy resin | Cutoff, U – RoW [1.20;1.02;1.03;1.00;1.20] Metal fasteners and nuts 1.05 4,2,2,1,3 steel production, chromium steel 18/8, hot rolled | steel, chromium steel 18 [1.20;1.02;1.03;1.00;1.20] Adhesives 1.05 4,2,2,1,3 bitumen adhesive compound production, hot | bitumen adhesive compound, hot | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Balsa wood 1.05 4,2,2,1,3 beam, hardwood, raw, kiln drying to u=10% | sawnwood, beam, hardwood, raw, dried (u=10%) | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Polyurethane foam 1.05 4,2,2,1,3 polyurethane production, flexible foam | polyurethane, flexible foam | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Protective coating (paint) 1.05 4,2,2,1,3 coating powder production | coating powder | Cutoff, U - RoW [1.20;1.02;1.03;1.00;1.20] Energy, diesel 1.05 1,4,1,1,1 market for diesel, burned in agricultural machinery | diesel, burned in agricultural machinery | Cutoff, U - GLO [1.00; 1.10; 1.00; 1.00; 1.00] Energy, gasoline 1.05 1,4,1,1,1 market for petrol, unleaded, burned in machinery | petrol, unleaded, burned in machinery | Cutoff, U - GLO [1.00; 1.10; 1.00; 1.00; 1.00] Energy, LPG 1.05 1,4,1,1,1 heat production, propane, at industrial furnace >100kW | heat, district or industrial, other than natural gas | Cutoff, U - RoW [1.00; 1.10; 1.00; 1.00; 1.00] Energy, ethanol c 1.05 1,4,1,1,1 ethanol production from sugarcane | ethanol, without water, in 95% solution state, from fermentation | Cutoff, U – BR; treatment of bagasse, from sugarcane, in heat and power co-generation unit, 6400kW thermal | heat, district or industrial, other than natural gas | Cutoff, U – GLO (without the fuel bagasse, from sugarcane) [1.00; 1.10; 1.00; 1.00; 1.00] Energy, electricity 1.05 1,4,1,1,1 market for electricity, low voltage | electricity, low voltage | Cutoff, U - BR [1.00; 1.10; 1.00; 1.00; 1.00] Transportation, truck 2.00 3,4,1,5,2 market for transport, freight, lorry, unspecified | transport, freight, lorry, unspecified | Cutoff, U - GLO [1.10;1.10;1.00;1.10;1.05] Transportation, ship 2.00 3,4,1,5,2 market for transport, freight, sea, transoceanic ship | transport, freight, sea, transoceanic ship | Cutoff, U - GLO [1.10;1.10;1.00;1.10;1.05] Output Losses (fiberglass and epoxy-impregnated material) 1.05 4,3,3,1,2 market for inert waste, for final disposal | inert waste, for final disposal | Cutoff, U - RoW [1.20;1.05;1.10;1.00;1.05] RoW: Rest of World. GLO: Global. *GSD2: relative squared geometric standard deviation. aPedigree matrix indicators: source reliability, completeness, temporal correlation, geographic correlation, and technology correlation, respectively. The inventory database was used (ecoinvent_case_studies_Ceramic_cup_vs_Paper_cup) with a method database (openLCA_LCIA_pack_2_1_3). bTextile production, jute | textile, jute | Cutoff, U – RoW was considered in the sensitivity analysis of the replacement of fiberglass by jute fiber grown without irrigation. cFor ethanol, the combination of two supplier inventories was considered: one representing the production of 0.0007 t of the fuel and the other representing the burning of 0.02 GJ of the fuel per blade. Equation A1 (Rosenbaum et al., 2018) combined the basic uncertainty and the pedigree uncertainties of each inventory flow: G S D X 2 : = e ∑ i = 1 n l n G S D X i 2 2 (A1) Equation A2 converted GSD2, representing a 95.45% confidence interval, into GSD, representing a 68% confidence interval: G S D X : = G S D X 2 (A2) Equation A3 (Ciroth et al., 2012) converted the combined uncertainty of each inventory flow into relative arithmetic standard deviation, or coefficient of variation (CV): C V X : = e l n G S D X 2 - 1 (A3) -Table A1) was inserted in openLCA® version 1.11.0 using the Ecoinvent™ inventory database version 3.4. The following evaluation methods were also used: ReCiPe 2016 midpoint (H) for water consumption (m3), cumulative energy demand (CED) for renewable and non-renewable energy consumption (GJ), and IPCC 2021 100-year global warming potential (GWP) for greenhouse gas (GHG) emissions in carbon dioxide equivalent (CO2eq). As a result, ReCiPe 2016 midpoint (H) was modified to include “water emission to water/unspecified emission,” since the database version used did not consider the water that returns to the water body.

2.3 Sensitivity and variability analysis

The National Electric System Operator of Brazilian data for 2021 was used in the first sensitivity analysis to assess the impact of the capacity factor on energy and environmental performance under three different scenarios: lower capacity factors and lifetime; average historical capacity factors and lifetime; and higher capacity factors and lifetime (ONS, 2022Operador Nacional do Sistema Elétrico – ONS. (2022). Dados da geração eólica. Retrieved in 2023, March 21, from http://www.ons.org.br/Paginas/resultados-da-operacao/boletim-geracao-eolica.aspx
http://www.ons.org.br/Paginas/resultados...
). The average capacity factor (MW/MW) of onshore wind turbines in Brazil for 2021 was 44%; the lowest value was 31% in March and the highest value was 58% in August (ONS, 2022Operador Nacional do Sistema Elétrico – ONS. (2022). Dados da geração eólica. Retrieved in 2023, March 21, from http://www.ons.org.br/Paginas/resultados-da-operacao/boletim-geracao-eolica.aspx
http://www.ons.org.br/Paginas/resultados...
). The average value in Brazil was higher than the global average for the onshore model, which ranged from 20% to 35% (Liu & Barlow, 2016Liu, P., & Barlow, C. Y. (2016). The environmental impact of wind turbine blades. IOP Conference Series. Materials Science and Engineering, 139, 012032. http://dx.doi.org/10.1088/1757-899X/139/1/012032.
http://dx.doi.org/10.1088/1757-899X/139/...
). The coastline between the states of Maranhão, Piauí, and Ceará has a 45% to 60% potential capacity factor for the offshore model (yet non-existent in Brazil). This information was considered in this study (Reis et al., 2021Reis, M. M. L., Mazetto, B. M., & Silva, E. C. M. (2021). Economic analysis for implantation of an offshore wind farm in the Brazilian coast. Sustainable Energy Technologies and Assessments, 43, 100955. http://dx.doi.org/10.1016/j.seta.2020.100955.
http://dx.doi.org/10.1016/j.seta.2020.10...
). Moreover, the average offshore capacity factor in Brazil was 53%.

The lifetime of a wind turbine blade is estimated to be 20 years (Cooperman et al., 2021Cooperman, A., Eberle, A., & Lantz, E. (2021). Wind turbine blade material in the United States: quantities, costs, and end-of-life options. Resources, Conservation and Recycling, 168, 105439. http://dx.doi.org/10.1016/j.resconrec.2021.105439.
http://dx.doi.org/10.1016/j.resconrec.20...
; Liu & Barlow, 2016Liu, P., & Barlow, C. Y. (2016). The environmental impact of wind turbine blades. IOP Conference Series. Materials Science and Engineering, 139, 012032. http://dx.doi.org/10.1088/1757-899X/139/1/012032.
http://dx.doi.org/10.1088/1757-899X/139/...
). According to EPE (2021)Empresa de Pesquisa Energética – EPE. (2021). Empreendimentos eólicos ao fim da vida útil – situação atual e perspectivas futuras. Brasília: Empresa de Pesquisa Energética. Retrieved in 2023, March 21, from https://www.epe.gov.br/sites-pt/publicacoes-dados-abertos/publicacoes/PublicacoesArquivos/publicacao-563/NT-EPE-DEE-012-2021.pdf
https://www.epe.gov.br/sites-pt/publicac...
, IEC 61400-1 (Wind energy generation systems – Part 1: Design requirements) suggests that the design of wind turbines has a minimum lifetime of 20 years, as this is the period considered in calculations, numerical modeling, laboratory tests with prototypes, mechanical strength testing of components, and field experiments that evaluate the history of equipment failures and breakdowns. The least desirable lifetime was 10 years, and the most desirable lifetime was 30 years.

In the second sensitivity analysis, the same mass quantity of jute fiber grown without irrigation was used in place of glass fiber to simulate the energy and environmental performance of the manufacture of wind turbine blades while maintaining all other parameters. The variability analysis was conducted to obtain the arithmetic standard deviation of the evaluated categories values from the Monte Carlo simulation with 500 interactions in openLCA®.

2.4 Electricity production

Due to variations in the capacity factor of wind turbine blades for different wind farms, wind farm electricity production (Eprod) was estimated to quantify the energy and environmental burden contribution per unit of production (GJ of electricity) over the lifetime of the wind farm. Eprod is a function of the number of turbines (n), the rated power (𝑃, in MW), the capacity factor (γ, in MW/MW), and the lifetime (ts, in years). The turbine model affects the nominal power. The ratio of the theoretical total power produced in continuous operation and the actual power production is the capacity factor. Equation 1 was used to estimate the energy production (in GJ), considering 365 days per year and a 24-hour operation per day:

E p r o d = n × P × γ × t s × 24 × 365 × 3.6 (1)

Eprod is 83 255 040 GJ for the onshore model and 100 284 480 GJ for the offshore model in the base scenario. Equation 2 was used to estimate the energy and environmental performance of the manufacture of wind turbine blades per GJ of electricity to be produced in the onshore and offshore wind farm.

D u D t E p r o d (2)

Where:

Du represents the unit performance of the rated category (category unit/GJ);

Dt represents the total performance of the evaluated category associated with the manufacture of wind farm blades (category unit);

Eprod represents the electricity to be produced in the wind farm life cycle (GJ).

3 Results

3.1 Energy and environmental performance

Figures 2 and 3 shows the material flow for the wind turbine blades of a wind farm with a nominal capacity of 300 MW. In total, 225 wind turbine blades were manufactured for the onshore model and 75 for the offshore model, and 870 973 m3 of water were consumed in the entire manufacturing process of wind turbine blades for the onshore model. The water consumption for the offshore model was 729 610 m3. Table 3 presents the contribution of water consumption per foreground inventory flow for the manufacture of all wind turbine blades needed to meet the demand of the evaluated wind farm.

Figure 2
Material flow analysis of wind farm blades (onshore model). The flows are classified as import (I) or export (E).
Figure 3
Material flow analysis of wind farm blades (offshore model). The flows are classified as import (I) or export (E).
Table 3
Contribution of water consumption of blades for onshore and offshore wind farms.

For both the onshore and offshore models, the energy consumption of wind turbine blades was similar, accounting for biomass, fossil, geothermal, nuclear, primary forest, solar, water, and wind contributions (Figure 4). For the onshore model, the wind turbine blades consumed 704 045 GJ of energy. Energy consumption for the offshore model was 629 815 GJ. Table 4 shows how much energy is consumed by each foreground inventory flow in relation to the wind turbine blade production.

Figure 4
Energy consumption of blades for onshore and offshore wind farms by source in GJ.
Table 4
Contribution of energy consumption of blades for onshore and offshore wind farms.

Table 5 presents the contribution of the manufacture of wind turbine blades to GHG emissions, broken down into foreground inventory flows.

Table 5
Carbon footprint of blades for onshore and offshore wind farms.

3.2 Sensitivity analysis

3.2.1 Influence of capacity factor and lifetime

Figure 5 shows the energy and environmental performance of the manufacture of wind turbine blades per GJ of electricity to be generated over the life cycle of onshore and offshore wind farms.

Figure 5
Energy and environmental performance of blades for onshore and offshore wind farms per electricity to be produced under different capacity factor and lifetime scenarios.

Compared to the least favorable scenario and the base scenario, which represents the historical average, the most favorable scenario for the onshore model shows a reduction of 83% in water consumption, 82% in energy consumption, and 82% in carbon footprint. In turn, the most favorable scenario for the offshore model presents a reduction of 79% in water consumption, 78% in energy consumption, and 78% in carbon footprint.

3.2.2 Substitute input for fiberglass fabric

When analyzing the life cycle of wind turbine blades, fiberglass contributed the most to water consumption (72% for onshore and 80% for offshore), energy consumption (61% for onshore and 64% for offshore), and the carbon footprint (67% for onshore and 69% for offshore). As a result, unirrigated jute fiber was used as a substitute input for fiberglass fabric in the evaluation of the energy and environmental performance of the manufacture of wind turbine blades. This reduced water consumption by 38% (onshore) and 42% (offshore), energy consumption by 18% (onshore and offshore), and the carbon footprint by 24% (onshore) and 25% (offshore) (Table 6).

Table 6
Performance of the manufacture of wind turbine blades with fiberglass and jute fiber grown without irrigation in the evaluated categories.

4 Discussion

Compared to the offshore model, onshore wind farms required three times as many wind turbine blades. However, the amount of waste generated in this model was 7.5% greater. Figures 2 and 3 suggest that even before the business is operational, the construction of a wind farm generates a significant amount of waste composite materials. In total, 500 t of composite materials would be generated for the evaluated scenarios in this study and these materials need to be properly treated. In a technical note, the Brazilian Ministry of Mines and Energy highlights the importance of measures to maintain, upgrade, or decommission wind farms to reduce their negative environmental effects once they have already served their purpose (EPE, 2021Empresa de Pesquisa Energética – EPE. (2021). Empreendimentos eólicos ao fim da vida útil – situação atual e perspectivas futuras. Brasília: Empresa de Pesquisa Energética. Retrieved in 2023, March 21, from https://www.epe.gov.br/sites-pt/publicacoes-dados-abertos/publicacoes/PublicacoesArquivos/publicacao-563/NT-EPE-DEE-012-2021.pdf
https://www.epe.gov.br/sites-pt/publicac...
). However, the document does not mention the amount of waste material generated during manufacturing that is impregnated with epoxy resin and fiberglass, and this issue should be treated in an environmentally responsible way.

Regarding manufacturing waste materials, the Caucaia West Metropolitan Sanitary Landfill (ASMOC – Aterro Sanitário Municipal Oeste de Caucaia) serves industries in the Pecém Industrial and Port Complex (CIPP) and is located 50 km away from the complex. Non-hazardous industrial solid waste is disposed in this landfill by the CIPP (Silva et al., 2017Silva, L. A., Abreu, M. C. S., & Diógenes, A. (2017). Gestão pública de resíduos sólidos industriais: avaliação institucional no complexo industrial e portuário do Pecém, Ceará. In XIX Encontro Internacional sobre Gestão Empresarial e Meio Ambiente (pp. 1-17). São Paulo: FEA/USP. Retrieved in 2023, March 21, from http://engemausp.submissao.com.br/19/anais/arquivos/276.pdf
http://engemausp.submissao.com.br/19/ana...
). When Giannetti et al. (2012)Giannetti, B. F., Bonilla, S. H., & Almeida, C. M. V. B. (2012). Cleaner production initiatives and challenges for a sustainable world. Journal of Cleaner Production, 22(1), I. http://dx.doi.org/10.1016/S0959-6526(11)00431-8.
http://dx.doi.org/10.1016/S0959-6526(11)...
analyzed the operation of a manufacturer of wind turbine blades in Sorocaba, São Paulo, they found that 10% to 15% of waste composite materials are disposed in the Sorocaba inert landfill. Similarly, Papadakis et al. (2010)Papadakis, N., Ramírez, C., & Reynolds, N. (2010). Designing composite wind turbine blades for disposal, recycling or reuse. In V. Goodship (Ed.), Management, recycling and reuse of waste composites (p. 443-457). Cambridge: Woodhead Publishing. http://dx.doi.org/10.1533/9781845697662.5.443.
http://dx.doi.org/10.1533/9781845697662....
reinforce that the waste generated in the manufacture of each wind turbine blade represents 10% of the mass of resin and fiber due to the cutting process of the resin-impregnated fiberglass materials. However, some countries in Europe have banned the use of landfills for this purpose. Law No. 1999/31/EC prohibits the landfilling of untreated fiber-reinforced polymer waste, stating that only biologically stabilized waste with low organic content may be landfilled (Kimm et al., 2020Kimm, M., Pico, D., & Gries, T. (2020). Investigation of surface modification and volume content of glass and carbon fibers from fiber reinforced polymer waste for reinforcing concrete. Journal of Hazardous Materials, 390, 121797. http://dx.doi.org/10.1016/j.jhazmat.2019.121797. PMid:31843401.
http://dx.doi.org/10.1016/j.jhazmat.2019...
). Due to their high organic content, Germany, for instance, banned the disposal of glass-fiber reinforced plastics in landfills in June 2005 (Larsen, 2009Larsen, K. (2009). Recycling wind. Reinforced Plastics, 53(1), 20-25. http://dx.doi.org/10.1016/S0034-3617(09)70043-8.
http://dx.doi.org/10.1016/S0034-3617(09)...
).

To dispose the composite materials waste in an environmental way, companies should change their business models. NEOCOMP is a licensed company located in Bremen, Germany, that recycles and uses fiber reinforced plastics (FRP) to create solid recovered fuel (SRF). FRPs are collected, cut, crushed, and mixed with other materials. In the cement factory, they are used in the cement kiln (Nagle et al., 2020Nagle, A. J., Delaney, E. L., Bank, L. C., & Leahy, P. G. (2020). A comparative life cycle assessment between landfilling and co-processing of waste from decommissioned Irish wind turbine blades. Journal of Cleaner Production, 277, 123321. http://dx.doi.org/10.1016/j.jclepro.2020.123321.
http://dx.doi.org/10.1016/j.jclepro.2020...
). The FRP is burned in a cement kiln which minimizes the need for coal or natural gas as a fuel and reduces carbon dioxide emissions by up to 16%. The leftover fiberglass is then combined with clay and limestone to make cement (EPRI, 2020Electric Power Research Institute – EPRI. (2020). Wind turbine blade recycling: preliminary assessment. Retrieved in 2023, March 21, from https://www.epri.com/research/products/000000003002017711
https://www.epri.com/research/products/0...
). Therefore, the 500 t of waste generated during the manufacture of the wind blades should be reduced at the source by cleaner production, and when inputs are wasted, they should be used in a higher added value way than simply being landfilled, for example, as a raw material for other processes such as cement manufacturing.

Most of the energy needed in the manufacture of wind turbine blades comes from non-renewable sources, with fossil fuels accounting for 86%, nuclear energy for 7%, and other sources for 7% (Figure 4). This outcome is similar to the study by Gomaa et al. (2019)Gomaa, M. R., Rezk, H., Mustafa, R. J., & Al-Dhaifallah, M. (2019). Evaluating the environmental impacts and energy performance of a wind farm system utilizing the life-cycle assessment method: a practical case study. Energies, 12(17), 3263. http://dx.doi.org/10.3390/en12173263.
http://dx.doi.org/10.3390/en12173263...
, which shows that large companies continue to rely primarily on fossil fuels for their energy needs.

Figure 5 suggests that increasing the capacity factor and lifetime of wind turbine blades reduces the amount of water, energy, and carbon dioxide (CO2) used in the production of each GJ of electricity to be produced in the wind farm. The scenario with the lowest carbon footprint (0.214 kg CO2eq/GJ) represents an offshore wind farm with a capacity factor of 60% MW/MW and a lifetime of 30 years. The least desirable scenario, on the other hand, represents the onshore model with a capacity factor of 31% MW/MW and a lifetime of 10 years (1.373 kg CO2eq/GJ). The most advantageous scenario shows a reduction of 84% in the carbon footprint when comparing these two scenarios. While Ahmad et al. (2021)Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: status quo, challenges and opportunities. Journal of Cleaner Production, 289, 125834. http://dx.doi.org/10.1016/j.jclepro.2021.125834.
http://dx.doi.org/10.1016/j.jclepro.2021...
point that power companies use drones to inspect blades in a safer and less expensive way, Yang et al. (2012)Yang, J., Peng, C., Xiao, J., Zeng, J., & Yuan, Y. (2012). Application of videometric technique to deformation measurement for large-scale composite wind turbine blade. Applied Energy, 98, 292-300. http://dx.doi.org/10.1016/j.apenergy.2012.03.040.
http://dx.doi.org/10.1016/j.apenergy.201...
suggest the use of videometry to assess the structural behavior of wind turbine blades on a large scale during the operation phase. The capacity factor is influenced by the site selection for the wind farm and depends on the availability of transmission lines to connect the energy produced to the National Interconnected System (SIN – Sistema Interligado Nacional), showing that government investments are needed to upgrade and build Brazilian power transmission systems (Diógenes et al., 2019Diógenes, J. R. F., Claro, J., & Rodrigues, J. C. (2019). Barriers to onshore wind farm implementation in Brazil. Energy Policy, 128, 253-266. http://dx.doi.org/10.1016/j.enpol.2018.12.062.
http://dx.doi.org/10.1016/j.enpol.2018.1...
; Herrera et al., 2019Herrera, M. M., Dyner, I., & Cosenz, F. (2019). Assessing the effect of transmission constraints on wind power expansion in northeast Brazil. Utilities Policy, 59, 100924. http://dx.doi.org/10.1016/j.jup.2019.05.010.
http://dx.doi.org/10.1016/j.jup.2019.05....
; Köberle et al., 2018Köberle, A. C., Garaffa, R., Cunha, B. S. L., Rochedo, P., Lucena, A. F. P., Szklo, A., & Schaeffer, R. (2018). Are conventional energy megaprojects competitive? Suboptimal decisions related to cost overruns in Brazil. Energy Policy, 122, 689-700. http://dx.doi.org/10.1016/j.enpol.2018.08.021.
http://dx.doi.org/10.1016/j.enpol.2018.0...
). The use of artificial intelligence (AI) supports real-time communication with wind farms regarding changes in wind direction and speed along with the status of the transmission grid. Thus, utilities can make the shutdown and startup of rotating parts more efficient, prevent unscheduled outages, and predict future maintenance needs based on the asset performance (Ahmad et al., 2021Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: status quo, challenges and opportunities. Journal of Cleaner Production, 289, 125834. http://dx.doi.org/10.1016/j.jclepro.2021.125834.
http://dx.doi.org/10.1016/j.jclepro.2021...
).

Jute fiber grown without irrigation can replace fiberglass supporting to reduce water consumption, energy consumption, and carbon footprint (Table 6). Plant fibers are less expensive, readily available, mechanically suitable, and impact-resistant materials that come from renewable resources (Silva Fo. et al., 2015Silva, R. S. S., Fo., Barbosa, V. C. S., Santana, A. L. M., Santos, E. B. C., & Amado, F. D. R. (2015). Desempenho da fibra natural de piaçava nas propriedades mecânicas de compósitos de matriz polimérica. In XX Congresso Brasileiro de Engenharia Química (pp. 8205-8212). São Paulo: Associação Brasileira de Engenharia Química. https://doi.org/10.5151/chemeng-cobeq2014-1103-20966-165215.
https://doi.org/10.5151/chemeng-cobeq201...
). They have gained popularity as a reinforcing material for FRPs due to their favorable mechanical qualities, high specific strength, non-abrasive nature, and low cost (Thomas & Ramachandra, 2018Thomas, L., & Ramachandra, M. (2018). Advanced materials for wind turbine blade- a review. Materials Today: Proceedings, 5(1), 2635-2640. http://dx.doi.org/10.1016/j.matpr.2018.01.043.
http://dx.doi.org/10.1016/j.matpr.2018.0...
). Summerscales (2021)Summerscales, J. (2021). A review of bast fibres and their composites: part 4 ~ organisms and enzyme processes. Composites Part A, Applied Science and Manufacturing, 140, 106149. http://dx.doi.org/10.1016/j.compositesa.2020.106149.
http://dx.doi.org/10.1016/j.compositesa....
states that the use of plant fibers extracted from plant stems as more environmentally friendly composite materials has increased.

In a literature review, we found studies that evaluated the use of various plant fibers to substitute fiberglass in wind turbine blades (Table 7).

Table 7
Summary of the types of plant fibers used to replace fiberglass in wind turbine blades found in the consulted literature review.

The findings in the consulted literature show many plant fiber alternatives to the fiberglass fabric currently used in wind turbine blades. The performance of wind turbine blades in terms of energy and the environment tends to benefit from the replacement of this input. Moreover, this replacement simplifies the recycling of the composite material produced during and after the lifetime of wind turbine blades, since besides being biodegradable, plant fiber-reinforced composites can be milled, reimpregnated, and reused at the end of their lifetime (Dorigato, 2021Dorigato, A. (2021). Recycling of thermosetting composites for wind blade application. Advanced Industrial and Engineering Polymer Research, 4(2), 116-132. http://dx.doi.org/10.1016/j.aiepr.2021.02.002.
http://dx.doi.org/10.1016/j.aiepr.2021.0...
). Brazil is abundant in all the plant-based materials mentioned in this section. For instance, bamboo is one of the fastest growing plants over a short period of time and is readily available in most tropical nations (Rassiah et al., 2014Rassiah, K., Ahmad, M. M. H. M., & Ali, A. (2014). Mechanical properties of laminated bamboo strips from Gigantochloa Scortechinii/polyester composites. Materials & Design, 57, 551-559. http://dx.doi.org/10.1016/j.matdes.2013.12.070.
http://dx.doi.org/10.1016/j.matdes.2013....
). On the other hand, plant fibers are sensitive to water, thus, the matrix polymer would provide long-term protection if these composites were used instead of fiberglass. They are also acceptable for the marine environment, as is the case for offshore application. Initial research with conventional marine thermoset matrix polymers suggests the possibility of creating a robust composite for marine applications (Davies et al., 2022Davies, P., Arhant, M., & Grossmann, E. (2022). Seawater ageing of infused flax fibre reinforced acrylic composites. Composites Part C: Open Access, 8, 100246. http://dx.doi.org/10.1016/j.jcomc.2022.100246.
http://dx.doi.org/10.1016/j.jcomc.2022.1...
). Therefore, investing in the development of a highly weather-resistant plant fiber suitable for use in wind turbine blades will allow Brazil to become a leader in the production of this type of product and reduce dependence on foreign inputs in a booming market in the country.

The evaluation of plant fiber research in the consulted literature (Table 7) was restricted to laboratory tests, prototypes, or small-scale turbine manufacturing. To meet the need for turbines in a wind farm, as is the case in this study, the implementation of wind turbine blades made of plant fibers on a commercial and industrial scale is necessary.

Regarding transportation, this study assumed that the materials were transported via the highway network from the Port of Santos to the manufacturer of wind turbine blades. Although the Port of Pecém is close to the manufacturing facility, the flow of ships between these ports is more expensive and less frequent. However, the quantity and quality of cabotage transport in Brazil is expected to increase and improve respectively, therefore, the logistics costs of using the maritime modal may become more beneficial after the approval of Law No. 14.301 (Brasil, 2022Brasil. Presidência da República. (2022, Januray 7). Lei nº 14.301, de 7 de janeiro de 2022. Institui o Programa de Estímulo ao Transporte por Cabotagem (BR do Mar); altera as Leis nºs 5.474, de 18 de julho de 1968, 9.432, de 8 de janeiro de 1997, 10.233, de 5 de junho de 2001, 10.893, de 13 de julho de 2004, e 11.033, de 21 de dezembro de 2004; e revoga o Decreto do Poder Legislativo nº 123, de 11 de novembro de 1892, e o Decreto-Lei nº 2.784, de 20 de novembro de 1940, e dispositivos da Medida Provisória nº 2.217-3, de 4 de setembro de 2001, e das Leis nºs 6.458, de 1º de novembro de 1977, 11.434, de 28 de dezembro de 2006, 11.483, de 31 de maio de 2007, 11.518, de 5 de setembro de 2007, 12.599, de 23 de março de 2012, 12.815, de 5 de junho de 2013, e 13.848, de 25 de junho de 2019 (seção 1, p. 1). Brasília, DF: Diário Oficial da República Federativa do Brasil. Retrieved in 2023, March 21, from https://www.planalto.gov.br/ccivil_03/_ato2019-2022/2022/Lei/L14301.htm
https://www.planalto.gov.br/ccivil_03/_a...
). Consequently, the energy consumption associated with the transportation of raw materials needed to produce wind turbine blades may greatly reduce.

Society benefits from the growth of wind energy in many ways, including greater energy security, a more diverse power grid, and less dependance on imported fossil fuels. Thus, incentives for the spread of the exploration and use of fossil fuels (oil, gas, and coal) should be removed and investment resources redirected from these sectors to increase the production and use of renewable sources (Grupo de Trabalho da Sociedade Civil para a Agenda 2030, 2021Grupo de Trabalho da Sociedade Civil para a Agenda 2030. (2021). V relatório luz da sociedade civil Agenda 2030 de desenvolvimento sustentável Brasil. Recife: Gestos – Soropositividade, comunicação e Gênero/Instituto Democracia e Sustentabilidade. ODS 7 energia limpa e acessível: assegurar acesso confiável, sustentável, moderno e a preço acessível à energia para todas e todos, pp. 46-50.) and expand wind energy. These actions contribute to achieve the sustainable development goals of the 2030 Agenda (UNDP, 2022United Nations Development Programme – UNDP. (2022). The SDGS in action. Retrieved in 2023, March 21, from https://www.undp.org/geneva/sustainable-development-goals
https://www.undp.org/geneva/sustainable-...
).

5 Conclusion

In order to build onshore and offshore wind farms with a nominal capacity of 300 MW, we evaluated the life cycle of the production of two types of wind turbine blades. The production of wind turbine blades results in a considerable amount of composite waste (around 500 t in this study). In Brazil, this material is usually disposed in landfills for industrial waste. However, this study showed that more advantageous approaches have been used to enable this waste to be disposed in an environmentally responsible way.

Most (93%) of the energy used in the entire life cycle of wind turbine blades comes from non-renewable sources. Fiberglass fabric influences water consumption (72% onshore and 80% offshore), energy consumption (61% onshore and 64% offshore), and the carbon footprint (67% onshore and 69% offshore) more than the other inputs. Moreover, the effect of road transport is significantly greater compared to sea transport. Even though the contribution of transportation was up to 10% in the categories analyzed, producing inputs near the manufacturing facility evaluated in this study supports the reduction of water consumption, energy consumption, and the carbon footprint of transportation.

According to the results of the sensitivity analysis, improving the capacity factors of wind farms and the lifetime of wind turbine blades should take precedence to reduce water consumption, energy consumption, and the carbon footprint per unit of electricity produced. Thus, government investments are needed to modernize and decongest the national power grid. Wind farms owners can extend the lifetime of their components by doing predictive and preventive maintenance on the wind turbine blades using sensors and drones. Manufacturers should highlight the importance of creating reliable wind turbine blades with high structural strength to withstand the fatigue cycles that the components undergo over their lifetime.

Jute fiber grown without irrigation had a lower water consumption, energy consumption, and carbon footprint than fiberglass when used as a substitute. Brazilian renewable resources can provide many plant fiber alternatives, including jute, bamboo, coconut, carnauba, and piassava. However, we found neither a wind farm using blades made of plant fibers nor a manufacturer producing them on a commercial scale. Thus, the possibility of creating a new product from a renewable, recyclable, and abundant source in Brazil that is more sustainable than most is great due to the advantages of this solution for the environment. However, to meet the demand of wind farms, further research is needed to assess the technological and financial viability of using plant fibers on an industrial scale.

Appendix 1 The basic uncertainty and pedigree score.

Table A1
Basic uncertainty and pedigree score of inventory flows.

Equation A1 (Rosenbaum et al., 2018Rosenbaum, R. K., Georgiadis, S., & Fantke, P. (2018). Uncertainty management and sensitivity analysis. In M. Z. Hauschild, R. K. Rosenbaum & S. I. Olsen (Orgs.), Life cycle assessment (pp. 271-321). Cham: Springer. http://dx.doi.org/10.1007/978-3-319-56475-3_11.
http://dx.doi.org/10.1007/978-3-319-5647...
) combined the basic uncertainty and the pedigree uncertainties of each inventory flow:

G S D X 2 : = e i = 1 n l n G S D X i 2 2 (A1)

Equation A2 converted GSD2, representing a 95.45% confidence interval, into GSD, representing a 68% confidence interval:

G S D X : = G S D X 2 (A2)

Equation A3 (Ciroth et al., 2012Ciroth, A., Muller, S., Weidema, B., Lesage, P., Berlin, G., & Montréal, C. (2012). Refining the pedigree matrix approach in ecoinvent: towards empirical uncertainty factors. Berlin: GreenDelta.) converted the combined uncertainty of each inventory flow into relative arithmetic standard deviation, or coefficient of variation (CV):

C V X : = e l n G S D X 2 - 1 (A3)
  • Financial support: None.
  • How to cite: Ramos Júnior, M. J., Medeiros, D. L., & Almeida, E. S. (2023). Blade manufacturing for onshore and offshore wind farms: the energy and environmental performance for a case study in Brazil. Gestão & Produção, 30, e12122. https://doi.org/10.1590/1806-9649-2022v29e12122

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Publication Dates

  • Publication in this collection
    22 May 2023
  • Date of issue
    2023

History

  • Received
    30 Jan 2023
  • Accepted
    21 Mar 2023
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