Life Cycle Assessment for the Energy Technologies: Issues and Challenges for Conventional and Hydrogen Energy
摘要
This paper presents examples of greenhouse Life Cycle Assessment (LCA) of three major fossil fuel-based energyEnergy sources: coal, natural gas (including liquefied natural gas, LNG), and petroleum diesel, focusing on their environmental impactsEnvironmental Impacts from extraction and processing to combustion and electricity generation and compare with complexity for hydrogenHydrogen fuel. The study evaluates greenhouse gas (GHG) emissions only, revealing that coal and petroleum diesel are the most environmentally damaging, with coal producing approximately 1,000 kg CO2-e per megawatt-hour (MWh) and diesel around 1,200 kg CO2-e per MWh. Natural gas, while offering a lower GHG footprint at about 600 kg CO2-e per MWh, presents challenges related to methane emissions and the energyEnergy-intensive processing when NG is converted to and used as LNG. The findings underscore the urgent need for policy interventions and technological advancements, such as carbon capture and storage (CCS) and high-efficiency, low-emission (HELE) technologies, to mitigate the environmental impactsEnvironmental Impacts of fossil fuels. This paper also highlights the impact of variable renewableVariable renewables energyEnergy (VRE) sources, such as solar and wind, on the carbon intensity of electricity and hydrogenHydrogen production. It concludes that conventionalConventional averaging methods for carbon intensity may not be adequate when VRE is part of the electricity grid. Instead, temporal resolution hourly, weekly, or monthly should be considered to accurately reflect the carbon footprint of hydrogenHydrogen and power generation. The paper concludes that the effect of temporal resolution is an important factor if VRE is part of the electricity grid. Thus, conventionalConventional averaging of the carbon intensity of electricity, hydrogenHydrogen produced, and subsequent power generated may not be sufficient for current LCA methods, modeling, and interpretation.