Mitigating climate disruption in time: A self-consistent approach for avoiding both near-term and long-term global warming.

Proceedings of the National Academy of Sciences of the United States of America(2022)

引用 28|浏览14
暂无评分
摘要
The ongoing and projected impacts from human-induced climate change highlight the need for mitigation approaches to limit warming in both the near term (<2050) and the long term (>2050). We clarify the role of non-CO2 greenhouse gases and aerosols in the context of near-term and long-term climate mitigation, as well as the net effect of decarbonization strategies targeting fossil fuel (FF) phaseout by 2050. Relying on Intergovernmental Panel on Climate Change radiative forcing, we show that the net historical (2019 to 1750) radiative forcing effect of CO2 and non-CO2 climate forcers emitted by FF sources plus the CO2 emitted by land-use changes is comparable to the net from non-CO2 climate forcers emitted by non-FF sources. We find that mitigation measures that target only decarbonization are essential for strong long-term cooling but can result in weak near-term warming (due to unmasking the cooling effect of coemitted aerosols) and lead to temperatures exceeding 2 °C before 2050. In contrast, pairing decarbonization with additional mitigation measures targeting short-lived climate pollutants and N2O, slows the rate of warming a decade or two earlier than decarbonization alone and avoids the 2 °C threshold altogether. These non-CO2 targeted measures when combined with decarbonization can provide net cooling by 2030 and reduce the rate of warming from 2030 to 2050 by about 50%, roughly half of which comes from methane, significantly larger than decarbonization alone over this time frame. Our analysis demonstrates the need for a comprehensive CO2 and targeted non-CO2 mitigation approach to address both the near-term and long-term impacts of climate disruption.
更多
查看译文
关键词
climate mitigation,fossil fuel radiative forcing,near-term warming,non-CO2 climate effects,short-lived climate pollutants
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