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As mentioned in section 2.3, this study focuses on the difference in climate effects between NDC and NP scenarios. Their carbon dioxide emissions are shown in red and orange in Fig. 1. In the NP scenarios, R5ASIA and R5OECD emit significantly more CO2 than other regions, followed by R5MAF, while the CO2 emissions of R5LAM and R5REF remain low for an extended time. Compared with the NP scenario, R5ASIA and R5OECD have the most prominent contributions to CO2 emission reduction, with cumulative emission reductions of 123.01 PgC and 106.89 PgC, respectively. The reductions of R5REF are rather small, which can also be seen in Fig. 3. The ranges of CO2 emissions under both the NP and NDC scenarios show significant growth after 2030. Although the ranges of CO2 emissions are affected by the simulation results of different IAMs, the ranges of CO2 mitigation are mainly derived from the variance of the NDC scenario. The other two scenarios (the 2-degree and 1.5-degree) are also shown in Fig. 1. These two ideal scenarios are significantly different from the NP and NDC scenarios. The carbon emissions scenario shows an overall downward trend, gradually reaching carbon neutrality in the future. The 2-degree scenario achieves carbon neutrality in 2062–78, while the 1.5-degree scenario achieves carbon neutrality ten to twenty years earlier than the 2-degree scenario. This is similar to the result of (van Soest et al. 2021), who reported the realization of carbon neutrality by 2065–80 (2-degree) and 2045–60 (1.5-degree). Obviously, to achieve the climate goals of the Paris Agreement, it is not sufficient to rely solely on the existing NDCs.
Figure 1. CO2 emissions of the R5 regions based on the CD-LINKS scenario dataset. Future CO2 emissions in the R5 region under four climate scenarios. The line is the average of the results of the five emission IAMs, and the shaded areas show the range of the scenario data. “NP”, “NDC”, and “2-degree” scenarios are marked by red, orange, and solid blue lines. The “1.5-degree” scenario is marked by green dashed lines. Pathways of other species (CH4, N2O, BC, and SO2) can be found in Fig. S1.
Figure 2. CH4, N2O, BC, and SO2 emissions of the R5regions based on the CD-LINKS scenario dataset. Future CH4, N2O, BC, and SO2 emissions in the R5 region in four climate scenarios. The line is the average of the results of the five emission IAM and the shade shows the range of the scenario data. “NP”, “NDC”, and “2-degree” scenarios are marked by red, orange, and blue solid lines. “1.5-degree” scenario is marked by green dashed lines.
Figure 3. The mitigation of CO2, CH4, N2O, BC, and SO2 emissions of the R5 regions based on the CD-LINKS scenario dataset. The map shows the regionalization (R5 regions) in this study. The bars around the map show emission reductions of NDC relative to NP scenarios. The cumulative reduction (for CO2, CH4, and N2O) or annual reductions (for BC and SO2) are shown here. The height of each column is a global emission difference, with the different colors representing the various R5 regions. The results are based on five IAMs are marked by different markers, and their average is shown with grey bars. The units are 100 PgC for CO2, 10 TgN for N2O, 1000 TgC for CH4, 0.01 TgC for BC, and 1 TgS for SO2 to plot the bars in one axis.
In addition to CO2, the pathways of CH4, N2O, BC, and SO2 are also considered in this study and used to drive the model. The cumulative reduction (for CO2, CH4, and N2O) or annual reductions (for BC and SO2) are shown in Fig. 3. Their emissions can be seen in Fig. 2. The region with the largest N2O emission reductions is the R5OECD, with an average of 19.59 TgN. R5OECD, R5ASIA, and R5LAM contribute significantly to CH4 emission reductions, with average emission reductions reaching 1975.36 TgC, 1627.76 TgC, and 1309.02 TgC, respectively. The critical regions for BC emission reduction are R5ASIA and R5LAM, both reaching approximately 0.02 TgC. SO2 is mainly reduced in R5ASIA, with an average of 0.57 TgS, accounting for more than 50% of global emission reductions. Notably, some data from specific IAMs show that the NDC scenario has larger regional emissions of some species than the NP scenario. For example, the emission reductions in R5REF obtained by the WITCH-GLOBIOM 4.0 simulation are small negative values except for CH4. The emission reduction of BC in R5OECD obtained by IMAGE 3.0.1 simulation is –0.31 TgC, which is quite different from the results of other IAMs. There may be some inconsistency in how clean air policies are assumed in the IAMs. The uncertainty of IAMs is considerable, although they are less important to climate change than CO2.
The increase in temperature and atmospheric CO2 relative to preindustrial times (~1850) is simulated by OSCAR v3.1, driven by the CO2, CH4, N2O, BC, and SO2 scenario datasets from CD-LINKS (Fig. 4 and Table 1). The average of the five IAMs shows that the global CO2 change relative to 1850 will reach 531.9±128.4 ppm in the NP scenario and 425.1±111.1 ppm in the NDC scenario in 2100. Adherence to NDC policy can avoid an increase of nearly 110 ppm in atmospheric CO2. Table 1 shows the increase in atmospheric CO2 (
$ \Delta {\mathrm{C}\mathrm{O}}_{2} $ ) simulated using scenario datasets from five IAMs. For the NP scenario, AIM/CGE 2.1 and IMAGE 3.0.1 result in an increase of approximately 500 ppm, while MESSAGEix-GLOBIOM 1.0, REMIND-MAgPIE 1.7-3.0, and WITCH-GLOBIOM 4.0 result in an increase of approximately 550 ppm. For the NDC scenario, the results are also different; that is, AIM/CGE 2.1 and REMIND-MAgPIE 1.7-3.0 optimistically yield less than 400 ppm, while MESSAGEix-GLOBIOM 1.0 results are almost as high as 500 ppm. Comparing the effects of NP and NDC, the estimation of atmospheric CO2 mitigation ranges from 56.05 ppm (MESSAGEEix-GLOBIOM 1.0) to 151.34 ppm (REMIND-MAgPIE 1.7-3.0). The range of$ \Delta {\mathrm{C}\mathrm{O}}_{2} $ for the NP scenario is 54.56 ppm, and that for the NDC scenario is 116.68 ppm. The range of CO2 mitigation calculated by the five IAMs is 95.29 ppm, significantly higher than that for the NP scenario. Therefore, the range of CO2 mitigation is mainly derived from the variance of the NDC scenario from IAMs.Figure 4. Atmospheric CO2 increase (
$ \Delta {\mathrm{C}\mathrm{O}}_{2} $ ) and temperature change ($ \Delta T $ ) relative to preindustrial (1850) simulations for scenarios. (a) The simulation of$ \Delta {\mathrm{C}\mathrm{O}}_{2} $ based on emission data from the five IAMs. The mitigation of$ \Delta {\mathrm{C}\mathrm{O}}_{2} $ induced by NDC relative to NP is marked and valued in the figures.$ \Delta {\mathrm{C}\mathrm{O}}_{2} $ in the 2-degree and 1.5-degree scenarios are also shown in the figures for comparison. (b) The same as (a), but for$ \Delta T $ . The mitigation of temperature increases is the core concern of this study and is attributed to regions in this study.Model NP NDC 2-degree 1.5-degree Future CO2 increase $ \Delta {\mathrm{C}\mathrm{O}}_{2} $ (ppm) AIM/CGE 2.1 502.20±122.34 380.78±93.59 132.61±30.85 94.89±22.57 IMAGE 3.0.1 504.66±118.69 426.50±102.01 143.03±35.40 93.31±23.09 MESSAGEix-GLOBIOM 1.0 553.51±126.24 497.46±117.21 122.43±33.05 82.85±22.42 REMIND-MAgPIE 1.7-3.0 542.64±132.83 391.30±100.34 124.01±32.08 84.63±22.56 WITCH-GLOBIOM 4.0 556.76±130.53 430.10±102.42 121.36±28.68 83.96±20.79 average 531.89±128.42 425.07±111.14 128.69±33.12 87.93±22.29 Future temperature changes $ \Delta \mathrm{T} $ (°C) AIM/CGE 2.1 4.10±0.92 3.52±0.81 1.91±0.51 1.57±0.45 IMAGE 3.0.1 3.91±0.89 3.49±0.80 1.96±0.53 1.62±0.45 MESSAGEix-GLOBIOM 1.0 4.01±0.90 3.74±0.85 1.79±0.51 1.43±0.43 REMIND-MAgPIE 1.7-3.0 4.20±0.95 3.40±0.80 1.89±0.52 1.59±0.45 WITCH-GLOBIOM 4.0 4.00±0.90 3.35±0.78 1.61±0.45 1.32±0.40 average 4.05±0.92 3.50±0.82 1.83±0.52 1.51±0.44 Table 1. Future CO2 increase (
$ \Delta {\mathrm{C}\mathrm{O}}_{2} $ ) and temperature changes ($ \Delta \mathrm{T} $ ) relative to 1850 in 2100.The temperature increases in the four scenarios are also simulated (Fig. 4b). If no climate policy is implemented, the temperature will rise by 4.1°C±0.9°C relative to the preindustrial level. With NDC implemented, the temperature increase is controlled at 3.5°C±0.8°C. Although there is still a large gap between the NDC scenario and the goals of the Paris Agreement, significant mitigations (0.6°C on average) are achieved, which is the core focus of this article. The temperature in the NP scenario simulated by all IAMs is significantly larger than that in the NDC scenario. The temperature mitigations are calculated as the difference between the NP and NDC emission scenarios from the same IAM (Fig. 4b), ranging from 0.3°C–0.8°C. To enhance the reliability of the results, we also calculate the transient climate response to cumulative carbon emissions (TCRE) in Fig. 5, which ranges from (1.54°C–1.94°C)/PgC, close to the estimates from the existing literature (Matthews, Gillett et al., 2009, Leduc, Matthews et al., 2016).
Figure 5. The transient climate response to cumulative carbon emissions (TCRE) in this study. The lines are the average of the results of 3000 simulations and the shades show the range of the simulated data. “NP”, “NDC”, “2-degree” and “1.5-degree” scenarios are marked by red, orange, blue and green dashed lines. We calculate the TCRE for NDC scenario and NP scenario as the slope. Considering the negative emissions of the 2-degree and 1.5-degree scenarios, we do not calculate the TCRE for these two scenarios.
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Furthermore, we attribute the temperature mitigation to regions according to the normalized marginal attribution method, in which relative contributions are proportional to the marginal climate effect of regional emission reductions. If only CO2 reduction is considered in the attribution, R5OECD and R5ASIA are the top two contributors, each accounting for more than 40% of the temperature mitigation on average (Fig. 6). The three IAMs conclude that R5OECD is the largest contributor, while the other two IAMs are more confident about R5ASIA (Table 2). R5LAM accounts for 10.9% of the temperature mitigation, on average, and is the third-largest contributor. The remaining temperature mitigation is attributed to R5REF and R5MAF, and their contributions are very small (no more than 5% on average).
Figure 6. The relative contributions of regions to climate mitigations with different climate forcers included. Each column represents the global climate mitigations (100%), with relative contributions from the R5 regions marked by different colors. “CO2”, “GHGs”, “GHGs + SO2”, “GHGs + BC”, and “all” labeled at the axis indicate which climate forcings are considered. GHGs refer to CO2, CH4, and N2O, and “all” refers to GHGs, BC, and SO2. The close-together columns represent results based on different IAMs, with the model average indicated by the red dashed lines. The five IAMs are AIM/CGE 2.1, IMAGE 3.0.1, MESSAGEix-GLOBIOM 1.0, REMIND-MAgPIE 1.7-3.0, and WITCH-GLOBIOM 4.0 (from left to right).
Model Region CO2 GHGs GHGs+BC GHGs+SO2 all AIM/CGE 2.1 ASIA 31.3 27.8 27.4 28.3 27.9 LAM 7.0 7.8 7.8 7.8 7.8 REF 4.0 3.8 3.8 3.8 3.8 OECD 51.2 51.6 51.9 51.2 51.4 MAF 6.4 9.0 9.1 9.1 9.2 IMAGE 3.0.1 ASIA 31.0 28.4 28.5 27.1 27.2 LAM 18.1 16.8 16.7 17.4 17.4 REF 2.3 4.9 4.8 4.8 4.8 OECD 36.8 34.6 34.3 36.0 35.7 MAF 11.9 15.4 15.7 14.7 15.0 MESSAGEix-GLOBIOM 1.0 ASIA 37.1 31.7 31.4 31.6 31.4 LAM 11.0 11.8 12.0 11.8 12.1 REF 0.5 2.1 2.0 2.2 2.1 OECD 51.1 52.7 52.5 52.6 52.4 MAF 0.2 1.8 1.9 1.8 2.0 REMIND-MAgPIE 1.7-3.0 ASIA 45.8 41.3 41.4 41.1 41.2 LAM 10.6 11.4 11.4 11.5 11.5 REF 1.1 3.3 3.3 3.4 3.4 OECD 40.2 36.0 35.8 36.1 36.0 MAF 2.4 7.9 8.0 7.9 8.0 WITCH-GLOBIOM 4.0 ASIA 69.5 56.6 56.6 56.2 56.2 LAM 7.8 8.9 8.9 9.0 9.0 REF −1.6 3.2 3.2 3.4 3.4 OECD 22.4 20.9 20.9 21.0 21.0 MAF 1.9 10.4 10.3 10.4 10.4 Table 2. The contributions of regional NDC to climate change mitigation (%).
Considering additional climate forcings, the relative contribution of temperature mitigation has changed. Considering all GHG reductions, R5MAF becomes much more important, accounting for an average of 8.9%. This is because the global CH4 and N2O reduction proportion of R5MAF is greater than that for CO2 (Fig. 3). Correspondingly, the share of R5ASIA dropped by approximately six percentage points, while the shares of R5OECD, R5LAM, and R5REF showed little change. In addition, we also included aerosols (BC and SO2) in the attribution. Although there are significant changes between aerosol-included attribution (“GHGs+BC”, “GHGs+SO2”, and “all” in Table 2) and aerosol-excluded attribution (“GHGs” in Table 2), they are very small. This is because GHGs have a long atmospheric lifetime, and cumulative emissions determine their climate effects. In contrast, the climate effects of short-lived aerosols are essentially determined by the current year’s emissions. Since the attribution is conducted for a long period (2014–2100), GHGs are much more important than aerosols in the mitigation attribution.
Considering “all” climate forcers in this study (CO2, CH4, N2O, BC, and SO2), R5OECD and R5ASIA represent the two major contributors to global warming mitigation, accounting for 39.3% and 36.8%, respectively. R5LAM and R5MAF followed R5OECD and R5ASIA, contributing 11.5% and 8.9%, respectively. R5REF only contributed 3.5%. The relative contributions depend on regional emission reductions but are not limited solely to CO2 emission reductions. Figure 7 shows that the regional contributions to climate mitigation are positively correlated with the CO2 emission reductions but are not completely linear. This is attributed to non-CO2 climate forcing and the nonlinear processes of the climate system. The reductions in other GHGs and SO2 are also worthy of attention, especially in certain regions, e.g., CH4 in R5MAF and SO2 in R5ASIA.
Figure 7. Pie charts for regional emission reductions and induced climate warming mitigations. (a) Pie charts for regional reductions in CO2, CH4, N2O, BC, and SO2. (b) The nested pie chart in the center of this figure shows the regional relative contributions when calculated with different amounts of substances considered. The center part of the nested pie chart shows the relative contributions calculated with only CO2 considered. The second layer, from the inside to the outside, considers CH4 and N2O in addition to CO2 (abbreviated as GHGs in this study). The third layer considers GHGs and BC, and the fourth layer considers GHGs and SO2. The outermost layer considers GHGs, BC, and SO2, referred to as “all” in this study.
Model | NP | NDC | 2-degree | 1.5-degree |
Future CO2 increase $ \Delta {\mathrm{C}\mathrm{O}}_{2} $ (ppm) | ||||
AIM/CGE 2.1 | 502.20±122.34 | 380.78±93.59 | 132.61±30.85 | 94.89±22.57 |
IMAGE 3.0.1 | 504.66±118.69 | 426.50±102.01 | 143.03±35.40 | 93.31±23.09 |
MESSAGEix-GLOBIOM 1.0 | 553.51±126.24 | 497.46±117.21 | 122.43±33.05 | 82.85±22.42 |
REMIND-MAgPIE 1.7-3.0 | 542.64±132.83 | 391.30±100.34 | 124.01±32.08 | 84.63±22.56 |
WITCH-GLOBIOM 4.0 | 556.76±130.53 | 430.10±102.42 | 121.36±28.68 | 83.96±20.79 |
average | 531.89±128.42 | 425.07±111.14 | 128.69±33.12 | 87.93±22.29 |
Future temperature changes $ \Delta \mathrm{T} $ (°C) | ||||
AIM/CGE 2.1 | 4.10±0.92 | 3.52±0.81 | 1.91±0.51 | 1.57±0.45 |
IMAGE 3.0.1 | 3.91±0.89 | 3.49±0.80 | 1.96±0.53 | 1.62±0.45 |
MESSAGEix-GLOBIOM 1.0 | 4.01±0.90 | 3.74±0.85 | 1.79±0.51 | 1.43±0.43 |
REMIND-MAgPIE 1.7-3.0 | 4.20±0.95 | 3.40±0.80 | 1.89±0.52 | 1.59±0.45 |
WITCH-GLOBIOM 4.0 | 4.00±0.90 | 3.35±0.78 | 1.61±0.45 | 1.32±0.40 |
average | 4.05±0.92 | 3.50±0.82 | 1.83±0.52 | 1.51±0.44 |