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Mitigation of China's carbon neutrality to global warming

Environmental Studies and Forestry

Mitigation of China's carbon neutrality to global warming

L. Li, Y. Zhang, et al.

Discover how China's carbon neutrality efforts can significantly affect global warming projections in the long term. This study, conducted by Longhui Li, Yue Zhang, Tianjun Zhou, Kaicun Wang, Can Wang, Tao Wang, Linwang Yuan, Kangxin An, Chenghu Zhou, and Guonian Lü, explores the nuanced impacts of China's climate strategies.

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Playback language: English
Introduction
Global warming, primarily driven by increasing atmospheric CO2 concentrations from fossil fuel combustion, poses significant threats to both natural systems and humanity. Limiting global mean temperature increase below 1.5 °C above preindustrial levels requires achieving net-zero CO2 emissions by 2055 and limiting non-CO2 greenhouse gas emissions. Over 120 countries have pledged to achieve carbon neutrality, making it crucial to quantify the impact of these pledges on future global warming. China, a major CO2 emitter, has committed to peaking carbon emissions before 2030 and achieving carbon neutrality before 2060. This study aims to quantify the mitigation effect of China's carbon neutrality (CNCN) on global warming using a fully coupled Earth system model, addressing the limitations of previous studies that employed simplified models. Understanding the magnitude of CNCN's contribution is essential for informing global climate mitigation strategies and promoting equitable development.
Literature Review
Existing literature has quantified the contributions of historical anthropogenic carbon emissions, but estimations vary based on different criteria. Studies using simplified climate models have estimated the avoided warming from China's carbon neutrality pledge, but a comprehensive assessment using a fully coupled Earth system model incorporating all crucial climate components was lacking. This research fills this gap by employing the NCAR Community Earth System Model (CESM) to provide a more robust quantification of CNCN's impact on global warming.
Methodology
The study utilizes the NCAR Community Earth System Model (CESM) version 2.1.3, a fully coupled Earth system model. Four pairs of simulations were conducted, each corresponding to a shared socioeconomic pathway (SSP): SSP1-2.6 (low emissions), SSP2-4.5 (intermediate), SSP3-7.0 (medium-high), and SSP5-8.5 (high emissions). Each pair consists of a default CMIP6 simulation and a CNCN scenario. In the CNCN scenario, anthropogenic surface CO2 emissions within China's domain were replaced with values consistent with the policy target of CNCN released by Tsinghua University in 2021. The equation used to modify the CO2 emissions is: CO2(i,j) = (CO2_CNN/CO2_SSP(i,j)) * CO2_SSP(i,j). Changes in CH4 and N2O emissions associated with CNCN (CNCNext) were also incorporated. The study examined changes in global mean surface temperature (GMST) over the near term (2021-2040), mid-term (2041-2060), and long term (2081-2100) relative to the preindustrial period (1850-1900). Paired t-tests were used to determine statistical significance. Spatial variations in temperature change were also analyzed.
Key Findings
China's carbon neutrality (CNCN) can individually mitigate global warming by 0.48 °C and 0.40 °C over the long term (2081-2100) under SSP3-7.0 and SSP5-8.5 scenarios, respectively. These mitigations account for 14% and 9% of the average increase in GMST. Incorporating CH4 and N2O emission changes (CNCNext) further reduces GMST by 0.21 °C and 0.32 °C for SSP1-2.6 and SSP2-4.5 over the long term. For SSP2-4.5, a reduction of 0.18°C is observed in the mid-term. The near-term impact of CNCN and CNCNext is insignificant for all SSPs. Spatial analysis reveals regional variations in temperature changes, with significant differences observed in specific regions, particularly in high latitudes over the long term. The avoided warming from CNCN is more pronounced in high-latitude regions under SSP3-7.0 and SSP5-8.5 scenarios, exhibiting a polar amplification pattern.
Discussion
The findings highlight the significant potential of China's carbon neutrality pledge to mitigate global warming, particularly in the long term and under high-emission scenarios. However, the relatively smaller impact in the near and mid-terms emphasizes the urgency of immediate global action. The inclusion of CH4 and N2O emission changes further underscores the importance of considering all greenhouse gases in climate mitigation efforts. The regional variations in temperature changes emphasize the complexity of climate interactions and the need for geographically tailored mitigation strategies. The results provide a valuable reference for the global stocktake under the Paris Agreement, highlighting the collective efforts needed from all countries to limit global warming.
Conclusion
This study provides the first comprehensive projection of the mitigation effect of a single country's carbon neutrality pledge on global warming using a fully coupled Earth system model. China's carbon neutrality pledge has the potential to significantly mitigate global warming, especially in the long term under high-emission scenarios. However, the limitations of the study, such as the assumption of no significant mitigation actions from other countries and the sensitivity of emission pathways to policy interventions and technological advancements, should be considered. Future research should incorporate these factors, as well as the impacts of atmospheric aerosols, to refine the estimations and increase the robustness of the findings. The study strongly supports the need for global collaborative efforts in climate mitigation.
Limitations
Several limitations affect the generalizability of the results. First, the model assumes other countries do not undertake significant mitigation actions, which is unrealistic. Second, the emission pathway used is just one possibility; pathways are sensitive to policy interventions and technological advancements. Third, the effects of atmospheric aerosols are not considered. Fourth, the model does not isolate China's unique contribution to warming, as global warming reflects cumulative anthropogenic emissions. Finally, using multiple simulations for each scenario would improve robustness by reducing internal variability uncertainty.
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