Future changes in the meteorological potential for winter haze over Beijing during periods of peak carbon emissions and carbon neutrality in China projected by Coupled Model Intercomparison Project Phase 6 models

Abstract

Hazy conditions have a significant impact on the environment and societal development. Their occurrence and persistence depend largely on climatological conditions, including the important role of climate change. Based on monthly data from 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) models under three Tier 1 scenarios (SSP1–2.6, SSP2–4.5, and SSP5–8.5), the meteorological potential for winter haze pollution over Beijing was assessed during periods of peak carbon emissions (PCP; 2021–2030) and carbon neutrality (approximate net‐zero emissions) (PCN; 2051–2060) in China. The results show that a possible high‐emission strategy during PCP may not obviously enhance winter hazy conditions over Beijing in the near future. Rather, the high‐emission scenario in this period may decrease the meteorological potential that is favourable for the enhanced Beijing haze pollution by inducing a Northeast Asia cyclonic anomaly, compared to situations under SSP2–4.5, with medium emissions. Further analyses indicated that, under the continued sustainable pathway (SSP1–2.6 in PCN plus SSP1–2.6 in PCP; the better pathway simulating the effects of approximate net‐zero emissions during PCN through model results), atmospheric conditions such as the East Asian winter monsoon as well as decadal oceanic forcings of the mega‐El Niño and the warm Atlantic Multidecadal Oscillation, which are conducive to more frequent Beijing haze, are significantly suppressed in the farther future PCN. Under such circumstances, in situ haze pollution is highly repressed, suggesting a critical and positive role for the low‐carbon policy advocated by China during PCN in suppressing longer‐term hazy conditions over Beijing. In contrast, Beijing haze pollution during PCN is frequent under the discontinued sustainable pathway (SSP2–4.5/SSP5–8.5 in PCN plus SSP1–2.6 in PCP). Our findings demonstrate the possible insignificant impact of the high‐emission strategy of China during the near‐future PCP on Beijing haze exacerbation, and an important role for carbon neutrality advocated by China to suppress the haze potential in the farther future PCN, highlighting the significance of future pathway selections.

Evaluation and projection of circulation conditions tied to summertime compound drought and heatwave frequency over the Yangtze River Delta, China, for the carbon neutrality period based on CMIP6 GCMs

“…The CMIP6‐involved GCMs featured higher horizontal resolutions and more sophisticated physical parameterizations (Eyring et al, 2016, 2019), including historical simulations for the period of 1850–2014 and future projections after 2015 (here, we use outputs from 2015 to 2100), driven by various SSP scenarios in the Scenario Model Intercomparison Projection (ScenarioMIP; Eyring et al, 2016; O'Neill et al, 2016). The projections of the variables in the climate system depend on the scenario (e.g., Chen et al, 2020; Deng et al, 2022; J. Wang et al, 2022). The SSP scenarios were updated from the RCPs of the previous CMIP5 to overcome scientific gaps (Stouffer et al, 2017; van Vuuren et al, 2011), resulting in more reasonable future scenarios by combining diverse social, economic and environmental developments (O'Neill et al, 2014).…”

“…This is because the MME mean was not only better than individual GCMs for the key variables (i.e., precipitation and Tasmax) in historical runs against the observations over the YRB but also reduced the uncertainties in the corresponding future projections (Yue et al, 2021). Such arithmetic averages across all model simulations and projections were extensively used to assess the performance of the CMIP6 models (e.g., J. Wang et al, 2022; Zha et al, 2023; Zhang & Chen, 2022). For fair comparisons with observations, the pressure‐level circulation data from CMIP6 outputs were bilinearly interpolated to a standard resolution of 2.5° × 2.5° before 9MME; meanwhile, the single‐level variables from CMIP6 outputs were bilinearly interpolated at a spatial resolution of T62 before 9MME, except for SM10cm, which was interpolated at a finer resolution of 1° × 1°.…”

“…Global climate models (GCMs) play a fundamental role in projecting the mean and extreme surface variables in China under various shared socioeconomic pathways (SSPs) for different future periods. These variables include wind speed (e.g., Wu et al, 2020; Zha et al, 2023), temperature and precipitation (e.g., Li et al, 2023; Sun et al, 2018; Xu et al, 2022; Yang et al, 2021; Yue et al, 2021), drought (e.g., Su et al, 2021) and haze (e.g., Cai et al, 2017; J. Wang et al, 2022). For example, by using GCMs from the Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6), Yue et al (2021) reported that, in the long term (2081–2100), the Tasmax averaged over the YRB is projected to increase by 1.75, 2.72 and 5.04°C under SSP scenarios SSP126, SSP245 and SSP585, respectively.…”