Opportunities to tackle short-lived climate pollutants and other greenhouse gases for China

Date Published
10/2022
Publication Type
Journal Article
Authors
DOI
https://doi.org/10.1016/j.scitotenv.2022.156842
Abstract

To limit the global temperature increase to below 1.5 °C, it is critical to reduce not only carbon dioxide (CO2), but also specific non-CO2 greenhouse gases (GHGs) and precursors, including some short-lived climate pollutants (SLCPs). These include emissions of black carbon, methane (CH4), tropospheric ozone, and fluorinated gases such as hydrofluorocarbons (HFCs). As the largest CH4 emitter and second-largest HFCs emitter, China plays a critical role in global efforts to reduce SLCPs and has acknowledged the need to reduce non-CO2 GHGs in its 2060 carbon neutrality goal. This study reviewed leading international experiences with SLCP reduction to identify global best practices to inform target development and policy actions in China and elsewhere. We used bottom-up modeling and scenario analysis to evaluate pathways of non-CO2 emission mitigation in China to 2050, drawing on mitigation measures developed through updated 2030 and 2050 cost curves. We identified a cost-effective reduction potential of 35 % for methane, 30 % for fluorinated gases, and 40 % for nitrous oxides—another potent GHG—in 2030 relative to 2015 levels for China under a Deep Non-CO2 Mitigation scenario. Annual total reduction potential of 1080 million metric tons of CO2 equivalent is also possible by 2030. For long-term targets, progress made on reducing SLCPs could help China reach its carbon neutrality target by 2060. While some uncertainties regarding the long-term mitigation potential of SLCPs remain, our analyses suggest that the fast adoption of available cost-effective technologies could allow China to reduce its non-CO2 GHGs by 56 % by 2050.

Notes

An open-access version of this article can be viewed here

Journal
Science of The Total Environment
Volume
842
Year of Publication
2022
URL
Organizations
Research Areas
Download citation