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Abstract Terrestrial ecosystems help mitigate global warming by sequestering atmospheric carbon dioxide (CO2) through plant photosynthesis, the rate of which is affected by surface ozone (O3) and aerosols under simultaneous impacts of climate change and rising CO2. While the changes in anthropogenic emissions perturb atmospheric components, their consequent impacts on ecosystem productivity in the future climate remain unclear. Here, we apply a fully coupled climate‐chemistry‐vegetation model, ModelE2‐YIBs, to explore the effects of O3 and aerosols from anthropogenic emissions on global gross primary productivity (GPP) under different emission scenarios at 2060. At the present day, anthropogenic air pollutants induce a GPP loss of −1.67 Pg[C] (−4%) in boreal summer with the contributions of −2.18 Pg[C] by O3 and +0.52 Pg[C] by aerosols. At 2060, the detrimental effect of air pollutants on GPP is exacerbated to −1.85 Pg[C] under a high emissions scenario but alleviated to −0.59 Pg[C] under a low emission scenario. The mitigated GPP loss in the latter scenario is owing to the effective control of anthropogenic emissions that on average reduces surface O3 concentrations by 8.14 ppbv globally relative to 2010. Although the CO2 fertilization effect is weaker in the low emission scenario, the strong decline in air pollutants brings additional GPP gains compared to the high scenario. Regionally, such GPP amelioration is close to or even overweighs the CO2 fertilization effect in eastern China and United States, suggesting that the deep cut of anthropogenic emissions can effectively promote future ecosystem productivity over the nowadays polluted regions.

Wetlands act as an important natural source of global methane (CH4). The emission rate of wetland CH4 is jointly affected by climate change, carbon dioxide (CO2) fertilization, and wetland distribution. In this study, we implemented a wetland CH4 emission module into the Yale Interactive Biosphere (YIBs) model to quantify the spatiotemporal variations of global wetland CH4 emissions in 2001–2020. Site-level validations showed that the YIBs model reasonably captures the seasonality and magnitude of CH4 emissions at 28 out of 33 sites with significantly positive correlations and low relative biases. On the global scale, the YIBs predicts an annual mean wetland CH4 emission of 147.5 Tg yr−1 in 2000–2017, very close to the estimate of 147.9 Tg yr−1 from the ensemble of 13 process-based models. Global wetland CH4 emissions showed a positive trend of 0.74 Tg yr−2 in the past 2 decades, leading to an increase of 7.4 Tg yr−1 (5.2%) in 2008–2017 than 2000–2009. Climate change and CO2 fertilization accounted for over 70% of global wetland CH4 emission changes. Among them, the impact of CO2 grew steadily and became the dominant factor after the year 2008. The most significant changes in wetland CH4 emissions were located in the tropical regions following the perturbations in temperature that drives the ecosystem productivity. We found limited changes in CH4 emissions over high latitudes because of the moderate variations in wetland area fraction. The rise of wetland CH4 emissions poses an emerging threat to the global warming and likely escalates the tropospheric air pollutants.

Despite many efforts to control anthropogenic sources, high ambient ozone (O _3 ) concentrations remain a serious air pollution problem in China. Terrestrial vegetation can remove surface O _3 through dry deposition but also enhance surface O _3 through biogenic volatile organic compound (BVOC) emissions. However, the net impacts of terrestrial vegetation on surface O _3 remains unclear. Here, we perform simulations using a chemistry-vegetation coupled model to assess the impacts of terrestrial vegetation on surface daily maximum 8 h average (MDA8) O _3 in China through biogeochemical processes, including BVOC emissions and stomatal uptake. The results show that vegetation biogeochemical processes increase summer mean surface MDA8 O _3 by 1.3 ppb in the present day in China, with 3.7 ppb from BVOC emissions but −2.7 ppb from stomatal uptake. However, the enhanced summer mean surface MDA8 O _3 from vegetation biogeochemical processes decreases from 5.4 to 2.7 ppb in the North China Plain (NCP), from 7.2 to 0.8 ppb in the Yangtze River Delta (YRD), from 8.7 to 1.8 ppb in the Sichuan Basin (SCB) and from 4.2 to 0.4 ppb in the Pearl River Delta by the period of carbon neutrality. Our study highlights that carbon neutrality-driven emission reductions can greatly mitigate the enhanced surface O _3 related to terrestrial vegetation, though there is still a positive impact of terrestrial vegetation on surface O _3 in some hotspots, including the NCP and the SCB.

Surface PM2.5 concentrations and aerosol optical depth (AOD) are two air pollution metrics tightly connected. Many studies have used AOD to derive PM2.5 concentrations without investigating their inconsistencies. Here, we explored the associations between surface PM2.5 and AOD using ground-level data from 19 stations in China during 2017–2019. Unexpectedly, we found low correlation coefficients of 0.03–0.60 between daily PM2.5 and AOD for most sites. Such decoupling between PM2.5 and AOD is further compared to simultaneous meteorological factors such as air temperature, specific humidity, sea level pressure, and wind speed. We found that specific humidity dominates the correlations with normalized PM2.5-AOD differences at 14 out of 19 sites. On average, specific humidity increases from 2.83 g kg−1 for the cases with low AOD but high PM2.5–11.89 g kg−1 for those with high AOD but low PM2.5, indicating that hygroscopic growth of aerosols may play an important role in decoupling the associations between PM2.5 and AOD. Random forest (RF) models using AOD as the only input yield a low R of 0.49 between the predicted and observed PM2.5 concentrations. The inclusion of specific humidity in the RF model increases the R to 0.74, close to the R of 0.81 with three additional meteorological factors. Our study revealed a strong decoupling between PM2.5 and AOD and suggested including specific humidity as a key parameter in the retrieval of long-term PM2.5 using AOD data in China.

Climate exerts both short-term and long-term impacts on the ecosystem carbon assimilation. However, the main climatic drivers for the variability of gross primary productivity (GPP) remain unclear across various timescales and vegetation types. Here, we combine the state-of-the-art machine learning algorithms with a well-established explanatory method to explore the impacts of climatic factors on long-term GPP variability at global FLUXNET sites across four timescales and six plant functional types. Results show that diffuse shortwave radiation (SWdif) dominates GPP variability at the sub-daily (half-hourly to three hourly) timescales especially for the tree species, and acts as the secondary contributor after air temperature at the daily or longer timescales. Attribution analyses further showed that the main effects of SWdif are much higher than their interactive effects with other climatic factors in regulating the GPP variability. By identifying the main climatic drivers, this study improves the understanding of the climate-driven GPP variability and provides important implications for the future projection of ecosystem carbon assimilation under global climate change.

To mitigate global warming and the resulting climate risk, many countries have accelerated the optimization of industrial structures and mixture of energy type in an attempt to achieve carbon neutrality by the second half of the 21st century. Here, we present the first assessment of the quantitative benefits of population exposure to extreme heat (defined by the heat index) during 2040–2049 under two scenarios of global carbon neutrality by 2060 and 2050, i.e. moderate green (MODGREEN) and strong green (STRGREEN) recovery scenarios, relative to the baseline scenario of Shared Socioeconomic Pathway (SSP) 2–4.5. Global mean extreme heat days increase by 12.1 d yr ^−1 (108%) during 2040–2049 under the SSP2-4.5 scenario relative to the historical period (1995–2014). The aggravating extreme heat events could be mitigated by as much as 12% and 18% during 2040–2049 under the MODGREEN and STRGREEN scenarios, respectively. Following the changes in extreme heat days, global population exposure to extreme heat is mitigated by 27.3 billion person-days (7%) in the MODGREEN scenario and 39.9 billion person-days (11%) in the STRGREEN scenario during 2040–2049 relative to the SSP2-4.5 scenario. Such benefits from these low-carbon policies are larger in regional hotspots, including India and Northern Africa, which have experienced high population growth and have extremely limited medical infrastructure. Moreover, an early carbon neutrality (2050 vs 2060) could avoid 12.6 billion person-days exposure to extreme heat during 2040–2049. Our results provide an important scientific support for governments to drive early policymaking for climate change mitigation.

The land ecosystems of China are estimated to provide an important sink for the increased atmospheric carbon dioxide (CO _2 ), but are undermined by severe ozone (O _3 ) pollution. Mitigation of O _3 damage to ecosystems remains a challenge considering that O _3 precursors are emitted from a wide range of anthropogenic sectors and O _3 formations are also affected by regional transport. Here, we combine chemical transport and dynamic vegetation models to quantify the benefits of sectoral and regional emission controls for the recovery of gross primary productivity (GPP) in the Yangtze River Delta (YRD). For sectoral emission controls, the largest mitigation of O _3 damage to GPP in YRD by 3.1 ± 0.4 and 2.2 ± 0.2 Gg[C] d ^−1 with 50% reductions in the emissions from industry and transportation sectors, respectively. For regional emission controls, reducing 50% anthropogenic emissions outside YRD can mitigate GPP losses by 18.6 ± 3.5 Gg[C] d ^−1 , larger than the recovery of 10.1 ± 1.6 Gg[C] d ^−1 by the 50% reductions of anthropogenic emissions within YRD. Moreover, summer months, especially July are the best period for GPP recovery from anthropogenic emission controls. Our results highlight the importance of sectoral and regional emission controls to mitigate O _3 damage to ecosystem productivities in YRD.