Australia-Japan Telecoupling of Wind Power-Based Green Ammonia for Passenger Transportation: Efficiency, Impacts, and Sustainability

SSRN Electronic Journal(2021)

引用 4|浏览6
暂无评分
摘要
Ammonia is a renewable energy medium appropriate for distant trading; therefore, many countries and companies have formulated ambitious strategies to develop energy transitions to use green ammonia for transportation systems. However, the associated social, economic and environmental impacts, and the overall viability and sustainability of these transitions are still a mystery, because of the lack of sufficiently complicated evaluations. To fill this gap, an integrated life cycle assessment and emergy evaluation (LCA-EME) method was developed and applied to synthesize, compare and recognize the hotspot nodes of resource depletion, emissions and impacts, and to quantify the exploitation and utilization efficiencies, environmental loadings and sustainability of the Australia-Japan telecoupling of wind power-based ammonia for electric vehicles (EV) and hydrogen fuel cell vehicles (FCV) used for passenger transportation, compared with two fossil fuel-based EV transportation systems. The results revealed that the transition to ammonia-based fuels can reduce nonrenewable energy consumption by >29.64% and Greenhouse Gas (GHG) emissions by >10.00%; however, the demand for emergy resources >2.03 times and biotic endpoint impacts >1.56 times, both of which mainly occurred in the sending subsystem of the telecoupling interaction. The results highlighted the necessity of internalizing the ‘external’ resource stress and its biotic impacts, increasing the utilization efficiency and the recycling rate of minerals and fresh water, and decreasing the endpoint impacts to guarantee the sustainability of the telecoupled energy transitions. Integrated LCA-EME was confirmed as a valuable tool for handling complex, multi-nodal nexus problems of telecoupling, which is widely needed for energy transition strategy making.
更多
查看译文
关键词
Resource depletion,Emissions,Biotic endpoint impacts,Efficiency,Sustainability
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要