AUTHOR=Fonseca Luiz Felipe Souza , Carvalho Monica TITLE=Greenhouse gas and energy payback times for a wind turbine installed in the Brazilian Northeast JOURNAL=Frontiers in Sustainability VOLUME=3 YEAR=2022 URL=https://www.frontiersin.org/journals/sustainability/articles/10.3389/frsus.2022.1060130 DOI=10.3389/frsus.2022.1060130 ISSN=2673-4524 ABSTRACT=Introduction

Going a step further than quantifying environmental impacts, establishing the environmental and energy payback times of a wind turbine can significantly impact the planning of a wind farm. This study applies the Life Cycle Assessment methodology to a wind turbine and verifies its environmental and energy payback times.

Methods

The Life Cycle Assessment was developed with the SimaPro software, using the Ecoinvent database and the IPCC 2013 GWP 100y and Cumulative Energy Demand environmental impact assessment methods. The Life Cycle Assessment considered the extraction of raw material, production of parts and pieces, transportation, assembly, use, and decommissioning. Besides the material composition of the wind turbine, meteorological data was also utilized to calculate wind electricity production in Northeast Brazil. The environmental analysis and data on energy production were used to calculate the time required to recoup the energy and emissions due to wind electricity compared to the emissions of the electricity grid.

Results

The emission factor of wind electricity was 0.0083 kg CO2-eq/kWh, and the emissions associated with consumption of electricity from the Brazilian Electricity mix was 0.227 kg CO2-eq/kWh. Consideration of the energy consumed for the manufacture of the wind turbine yielded an energy payback of 0.494 years, and greenhouse gas accountancy led to a payback of 0.755 years.

Discussion

The results demonstrate that the payback periods are much lower than the lifetime of the wind turbine, highlighting the important role in addressing climate change and energy savings. The combination of Life Cycle Assessment and energy and environmental paybacks can be used to measure sustainability and deploy wind energy projects in locations with the shorter payback times.