Paris-compatible Emission Targets for the Six Major Emitters

Paris-compatible Emission Targets for the Six Major Emitters based on the Extended Smooth Pathway Model (ESPM) 1 DOI 10.5281/zenodo.17206418 Published on zenodo Version: 26/09/2025 EDGAR data status: September 2025 Prof. Manfred Sargl Dr. Daniel Wiegand Günter Wittmann Andreas Wolfsteiner www.save-the-climate.info ● [email protected] Web apps for this paper: • Paris-compatible national CO2 budgets: https://national-budgets.climate-calculator.info • Emission paths: https://paths.climate-calculator.info • National CO2 budgets derived from NDCs: https://ib-iwp.climate-calculator.info Abstract What are achievable territorial emissions targets for the world's six major emitters that sum up to Paris-compatible emissions? To answer this question, this paper varies key global framework data on the available budget and the sharing mechanism to calculate top-down national emissions targets using the Extended Smooth Pathway Model (ESPM). The Paris Ratchet Mechanism is based on a bottom-up approach. However, if the national targets are not Paris-compatible in sum, the question arises whether they represent an adequate contribution to the necessary global efforts. An open and transparent discussion of this issue can contribute to NDCs that, in sum, are once compatible with the Paris Agreement. 1 This paper is also an update of a publication in the "Zeitschrift für Umweltpolitik & Umweltrecht" (Sargl, et al., 2021) due to the publication of new data on the remaining global budgets in the Sixth Assessment Report of the IPCC (IPCC, 2021) and emissions data (EDGAR, 2025). See also our corresponding paper for Germany and the EU (Sargl, et al., 2025). Calculation of Paris-compatible Emission Targets with the ESPM Page 2 / 42 Content Abstract ........................................................................................................................................... 1 Lists of Tables, Figures and Excursuses ......................................................................................... 3 1 Global CO2 budgets and their relevance for national targets..................................................... 4 2 Calculation of national emission paths with the ESPM ............................................................. 6 2.1 The Extended Smooth Pathway Model (ESPM) ............................................................... 6 2.1.1 Determining of national budgets ............................................................................. 6 2.1.2 Derivation of national emission paths ..................................................................... 7 2.1.3 NDC indicator: Implicit weighting of the population (IWP) .................................. 7 2.2 Data basis used ................................................................................................................... 9 3 Current emission targets of the six largest emitters.................................................................. 11 4 Exemplary national emission targets for the six largest emitters plus Nigeria ........................ 14 4.1 Overview of results for extreme and mean values in the global framework data ............ 14 4.2 Exemplary global framework data reflect the NDCs of USA, EU and Japan ................. 19 4.3 Exemplary global framework data reflect the NDCs of China and India ........................ 25 5 Conclusions .............................................................................................................................. 28 Tools and further exemplary results .............................................................................................. 30 Excursuses ..................................................................................................................................... 31 References ..................................................................................................................................... 38 Appendix: Exemplary national budgets with different global framework data ............................ 42 Calculation of Paris-compatible Emission Targets with the ESPM Page 3 / 42 Lists of Tables, Figures and Excursuses List of Tables Tab. 1: Remaining global CO2 budgets from 2020 onwards with a compliance probability of 83% ............................. 4 Tab. 2: Baseline data of the six largest emitters plus Nigeria .......................................................................................... 9 Tab. 3: Calculation scheme of the global budget to be distributed here ........................................................................ 10 Tab. 4: Current emission targets of the six largest emitters........................................................................................... 11 Tab. 5: Conversion NDCs to the change in 2030 compared to 2019 ............................................................................ 12 Tab. 6: Implicit budgets and weightings population (IWP)........................................................................................... 13 Tab. 7: Linear emission paths - reference values big six - B300 / P100 / NNE0 / LUC0 ............................................. 15 Tab. 8: Linear emission paths - reference values big six - B650 / P100 / NNE0 / LUC0 ............................................. 15 Tab. 9: Linear emission paths - reference values big six - B650 / P50 / NNE0 / LUC0 ............................................... 16 Tab. 10: Linear emission paths - reference values big six - B650 / P0 / NNE0 / LUC0 ............................................... 16 Tab. 11: Linear emission paths - reference values big six - B650 / P50 / NNE25 / LUC180 ....................................... 18 Tab. 12: Linear emission paths - reference values big six – B550 / P15 / NNE2 / LUC0 ............................................. 19 Tab. 13: Comparison with NDCs (change 2030 vs. 2019) - B550 / P15 / NNE2 / LUC0 ............................................ 19 Tab. 14: Comparison with NDCs (budgets) - B550 / P15 / NNE2 / LUC0 ................................................................... 20 Tab. 15: RM Scenario Types - reference values China - B550 / P15 / NNE2 / LUC0 .................................................. 20 Tab. 16: RM Scenario Types - reference values USA - B550 / P15 / NNE2 / LUC0 ................................................... 21 Tab. 17: RM Scenario Types - reference values EU - B550 / P15 / NNE2 / LUC0 ...................................................... 22 Tab. 18: RM Scenario Types - reference values India - B550 / P15 / NNE2 / LUC0 ................................................... 22 Tab. 19: RM Scenario Types - reference values Russia - B550 / P15 / NNE2 / LUC0................................................. 23 Tab. 20: RM Scenario Types - reference values Japan - B550 / P15 / NNE2 / LUC0 .................................................. 23 Tab. 21: RM Scenario Types - reference values Nigeria - B550 / P15 / NNE2 / LUC0 ............................................... 24 Tab. 22: RM Scenario Types - reference values China – B650 / P15 / NNE25 / LUC180 ........................................... 26 Tab. 23: RM Scenario Types - reference values India – B650 / P15 / NNE25 / LUC180 ............................................ 26 Tab. 24: Linear emission paths - reference values big six – B650 / P15 / NNE25 / LUC180 ....................................... 27 Tab. 25: Comparison with NDCs (budgets) – B650 / P15 / NNE25 / LUC180 ............................................................ 27 Tab. 26: GDP per capita of the six largest emitters ....................................................................................................... 34 Tab. 27: Exemplary national budgets with different global framework data ............................................................... 42 List of Figures Fig. 1: Paris-compatible global emission paths – B650 .................................................................................................. 5 Fig. 2: Emission paths major emitters (RM-6-abs) – B650 / P50 / NNE0 / LUC0 ....................................................... 17 Fig. 3: Weighting population vs. targets 2030/2019 major emitters – B650 / NNE0 / LUC0 ....................................... 18 Fig. 4: RM Scenario Types – emission paths and annual change rates China – B550 / P15 / NNE2 / LUC0 ............... 21 Fig. 5: RM Scenario Types – emission paths and annual change rates EU – B550 / P15 / NNE2 / LUC0 ................... 22 Fig. 6: RM Scenario Types – emission paths and annual change rates Nigeria – B550 / P15 / NNE2 / LUC0 ............ 24 Fig. 7: Emission paths major emitters (RM-3-lin) – B550 / P15 / NNE2 / LUC0 ........................................................ 25 Fig. 8: RM Scenario Types – emission paths and annual change rates China – B650 / P15 / NNE25 / LUC180 ......... 26 Fig. 9: RM Scenario Types – emission paths and annual change rates India – B650 / P15 / NNE25 / LUC180 .......... 27 Fig. 10: Allocation principles for the distribution of a remaining global CO2 budget .................................................. 33 List of Excursuses Excursus 1: German Federal Constitutional Court on CO2 budgets ............................................................................. 32 Excursus 2: German Federal Constitutional Court on freedom opportunities for future generations ........................... 32 Excursus 3: Allocation of a global CO2 budget ............................................................................................................ 35 Excursus 4: Potential for emissions trading between countries ..................................................................................... 36 Excursus 5: Regensburg Model Scenario Types ........................................................................................................... 37 Calculation of Paris-compatible Emission Targets with the ESPM Page 4 / 42 1 Global CO2 budgets and their relevance for national targets CO2 accumulates in the atmosphere. 2 If global warming is to keep within certain limits, the sum of CO2 emissions is therefore decisive (budget property of CO2). Fig. 1 makes clear what also results from the budget property: the later we act, the earlier we have to achieve emission neutrality and the more we depend on net negative emissions. Overarching goal in the Paris Agreement is to hold "the increase in the global average temperature to well below 2°C above pre-industrial levels" and pursue efforts "to limit the temperature increase to 1.5°C above pre-industrial levels". For the remaining global CO2 budgets, the IPCC published the figures in Tab. 1 in its Sixth Assessment Report 2021: Warming Remaining carbon budgets [°C] [GtCO2 from 2020 on] 1.5 300 1.6 400 1.7 550 1.8 650 Tab. 1: Remaining global CO2 budgets from 2020 onwards with a compliance probability of 83% 3 In 2024, global emissions were estimated at around 42 GtCO2 (GCP, 2024). The need to take into account the socio-economic consequences of the pace of decarbonisation, the likelihood of compliance and other uncertainties requires a science-based but ultimately policy decision on the global carbon budget against which nationally determined contributions (NDCs) are set. If the Parties make transparent an underlying global CO2 budget and its distribution in their NDCs, or if they are more encouraged to do so, this can initiate a discourse that ultimately leads to converging benchmarks for the global framework data that contributes to Paris-compatible NDCs in sum. 4 2 The subscript of 2 in CO2 is omitted in this work for reasons of simplification. 3 Tab. 1 based on Table SPM.2 in the IPCC Sixth Assessment Report (cf. IPCC, 2021). The key statements of the IPCC on remaining CO2 budgets are summarised here: (Wolfsteiner, 2025c). New data on the remaining CO2 budget will also be presented there. For further background information, we refer to the IPCC report. 4 In a landmark decision in 2021 the Federal Constitutional Court in Germany made this clear: Climate policy must be oriented towards remaining CO2 budgets (cf. BVerfG, 2021). This results from the physically given budget property of CO2. See also Excursus 1: German Federal Constitutional Court on CO2 budgets. Calculation of Paris-compatible Emission Targets with the ESPM Page 5 / 42 Fig. 1: Paris-compatible global emission paths – B650 5 5 All paths adhere to a CO2 budget of 650 Gt in the period 2020 – 2100. -5 Gt was specified as the possible minimum for emissions. A starting change rate of 0.5% was selected in the RM Scenario Types 3 – 5. For the scenario types used, see Excursus 5. The paths were calculated with this tool: (Wolfsteiner & Wittmann, 2025c). This refers to total CO2 emissions, including land use change (actual values according to (GCP, 2024)). Here are simplified web apps: • RM Scenario Types (see Excursus 5): https://paths.climate-calculator.info • Linear global emission paths: http://global-paths.climate-calculator.info Calculation of Paris-compatible Emission Targets with the ESPM Page 6 / 42 2 Calculation of national emission paths with the ESPM 2.1 The Extended Smooth Pathway Model (ESPM) In order to calculate national emission targets based on global framework data, the Extended Smooth Pathway Model (ESPM) is used. The ESPM proceeds in two steps (cf. Wiegand, et al., 2021; Sargl, et al., 2021): 1. Determining of national budgets 2. Derivation of national emission paths 2.1.1 Determining of national budgets In order to derive national budgets from a global budget, an allocation key is needed. In determining the following exemplary national emissions targets, a weighted distribution key was used that takes into account a country's share of global emissions and its share of the world's population in 2019 (cf. Raupach, et al., 2014). 6 With this two-dimensional distribution key, the current emissions reflect the current reality and the population shares address the issue of climate justice. This leads to the following weighting formula: 𝐵𝑖=(𝐶∗𝑃𝐵𝑌 𝑖 𝑃𝐵𝑌 +(1−𝐶)∗𝐸𝐵𝑌 𝑖 𝐸𝐵𝑌)∗𝐵 where 𝐸𝐵𝑌 𝑜𝑟 𝐸𝐵𝑌 𝑖 global emissions or emissions of country i in the base year; here: BY = 2019 𝑃𝐵𝑌 𝑜𝑟 𝑃𝐵𝑌 𝑖 global population or population of country i in the base year 𝐵 or 𝐵𝑖 global CO2 budget or national CO2 budget of the country i; here from 2020 on 𝐶 weighting of population 7 There are many possible approaches to allocating a global budget to countries (cf. van der Wijst, et al., 2025). In our view, this distribution key represents the most important factors and makes it possible in particular to identify feasible national targets. Other criteria seem to us to make more sense in other contexts (see Excursus 3: Allocation of a global CO2 budget). A two-dimensional distribution key also has the advantage that only one factor has to be determined. 6 In some of our tools, it is also possible to specify national budgets that have been determined in a different way (see Chapter “Tools and further exemplary results "). 7 Based on converging per capita emissions, an implicit weighting of the population can be determined in the Regensburg Model (cf. Sargl, et al., 2017; Sargl, et al., 2024a). This is one way to identify a traceable value (cf. Wolfsteiner & Wittmann, 2024b). Calculation of Paris-compatible Emission Targets with the ESPM Page 7 / 42 2.1.2 Derivation of national emission paths With the help of the Regensburg Model Scenario Types RM 1 – 6, plausible emission paths are derived that comply with the national CO2 budget. With these scenario types, we offer the entire range of plausible possibilities (see Excursus 5). A volume overshoot can be taken into account in the RM Scenario Types. This means a temporary exceeding of the previously defined CO2 budget. This overshoot is offset by subsequent net negative emissions until 2100. 8 The potential for net negative emissions is included in the model by a percentage of a country's emissions in 2019. 9 The result represents the potential minimum emissions by 2100. If this value is negative, then a volume overshoot is possible. Thereby, the lower this negative value, the higher the overshoot. The illustrative model pathways P1 – P4 of the IPCC from its 2018 special report can be used as a reference for the potential for a volume overshoot. However, the corresponding values show a wide range. CO2 emissions in 2100 excluding land use (AFOLU) relative to corresponding emissions in 2019 range from -55% to +2% (cf. Wolfsteiner & Wittmann, 2025e; Wolfsteiner & Wittmann, 2025c). 10 2.1.3 NDC indicator: Implicit weighting of the population (IWP) Countries indirectly point out with their NDC which national CO2 budget they are claiming for themselves in the future. The implicit weighting of the population (IWP) is a helpful measure for assessing this claim (cf. Sargl, et al., 2024a; Wolfsteiner & Wittmann, 2024b; Wolfsteiner, 2025b). If this national budget 8 The following main aspects need to be considered (cf. Wolfsteiner & Wittmann, 2025e): (1) In order to achieve climate neutrality, unavoidable methane and nitrous oxide emissions from agriculture, for example, must be offset by negative CO2 emissions. These must be provided in addition to the net negative CO2 emissions assumed here. (2) At present, the potential of negative emissions is very uncertain technically, economically and in terms of their durability (cf. SRU, 2020). (3) Even if a budget is met that corresponds to the targeted limitation of global warming, a temporary volume overshoot can lead to the overshooting of tipping points in the climate system. (4) According to recent findings, “the century-scale climate–carbon cycle response to a CO2 removal from the atmosphere is not always equal and opposite to the response to a CO2 emission” (IPCC, 2021, p. 9 chapter 5). This potential asymmetry is not taken into account here. 9 This means that countries with high current emissions would have to realise or finance high net negative CO2 emissions. Since a budget for LUC is provided here at global level, negative CO2 emissions at national level refer to the non-LUC sector. 10 It should be expressly noted that net negative emissions in the IPCC illustrative model paths can also serve to offset positive emissions of other greenhouse gases such as methane and nitrous oxide, and not just to offset past CO2 overshoot. Calculation of Paris-compatible Emission Targets with the ESPM Page 8 / 42 can be estimated (cf. Wolfsteiner, 2025a) or, at best, is even directly specified, the implicit weighting of the population depending on a global CO2 budget is given by C= 𝐵𝑖−𝐵∗𝐸𝐵𝑌 𝑖𝐸𝐵𝑌 ⁄ 𝐵∗(𝑃𝐵𝑌 𝑖𝑃𝐵𝑌 ⁄−𝐸𝐵𝑌 𝑖𝐸𝐵𝑌) ⁄=𝐼𝑊𝑃 after transforming the above weighting formula. See Tab. 6 for the IWP for the six major emitters based on their NDCs. Calculation of Paris-compatible Emission Targets with the ESPM Page 9 / 42 2.2 Data basis used The EU database EDGAR provides CO2 emissions excluding CO2 emissions from land-use (LUC) and international shipping and aviation (ISA) for all countries in the world which are shown in Tab. 2 for the six largest emitters plus Nigeria (cf. EDGAR, 2025). 11 For comparison Nigeria is added as an example of a country with low per capita emissions and a low share of global emissions. emissions in Gt per capita 2019 in t share in global emissions 2019 share in global population 2019 1990 2010 2019 2024 China 2.4 9.1 11.8 13.1 8.3 32% 18% United States 5.0 5.5 5.0 4.6 15.1 14% 4% EU27 3.8 3.4 2.9 2.5 6.6 8% 6% India 0.6 1.7 2.6 3.2 1.9 7% 18% Russia 2.4 1.7 1.9 2.0 12.9 5% 2% Japan 1.2 1.2 1.1 1.0 8.9 3% 2% Sum 15.4 22.7 25.2 26.4 69% 50% Nigeria 0.08 0.09 0.13 0.13 0.6 0.3% 2.6% Global 22.0 32.8 36.7 39.6 4.8 100% Tab. 2: Baseline data of the six largest emitters plus Nigeria 12 11 Brief description of different concepts CO2 emission from land use: GCP LUC = CO2 from land use changes, IPCC AFOLU = agriculture + forestry + land use, UNFCCC/EU LULUCF = essentially CO2 from land use & forests. AFOLU and LULUCF are almost identical in regard to CO2 in theory, as agriculture almost exclusively involves CH₄/N₂O. When using the remaining carbon budgets presented by the IPCC, it is important to offset all anthropogenic CO2 emissions. This includes not only emissions from fossil fuels and industrial processes (EFOS), but also emissions from land use changes. The Global Carbon Project (GCP) LUC category is the appropriate measure to be used here (GCP, 2024), because AFOLU-CO2 (IPCC) and LULUCF (UNFCCC/EU) include not only land use changes but also management-related sinks (e.g. forest management, wood products). These sinks are already accounted for in the IPCC budget framework as part of the natural land sink. However, in the IPCC illustrative model paths, AFOLU CO2 emissions only reflect sources from land use changes (cf. IPCC, 2019, sec. 2.3.1.2). Management-related sinks (forests, soils, HWP) are reported separately as land sinks. Therefore, LUC according to GCP largely corresponds to AFOLU emissions in the IPCC illustrative model paths. The following are the estimated emissions for 2010: concept model path IPCC SR15 GtCO2 source LUC +5.5 (GCP, 2024) LULUCF -2.6 (EDGAR, 2025) AFOLU IPCC SR15 P1 +5.4 (Wolfsteiner & Wittmann, 2025c) P2 +4.6 P3 +7.2 P4 +4.2 12 These are the CO2 emissions from fossil fuel use (except international shipping and aviation; ISA) and cement production (EDGAR, 2025). CO2 emissions from land-use change (LUC) are therefore not included here (see also Chapter 2.2 Data basis used). Remark: The countries (excluding the EU) that account for less than 2% of global CO2 emissions are together responsible for around 39% of global emissions. This means that even countries with a small share of global emissions cannot escape responsibility. Calculation of Paris-compatible Emission Targets with the ESPM Page 16 / 42 the target is reduced to 1.8°C, which can be understood as the lower limit of the Paris Agreement. With a global CO2 budget that is seriously geared towards limiting global warming to 1.5°C, China, USA, Russia and Japan would no longer be able to meet their budget due to their actual emissions since 2019 (see Tab. 7). Weighting the factors population and emissions equally leads to the results in Tab. 9 and the results of a population weighting of 0% (grandfathering) are shown in Tab. 10. global CO2 budget 2020 - 2100 in Gt 650 minimum annual emissions 0% weighting population 50% LUC budget 2020 - 2100 in Gt 0 reference values (linear emission paths, RM-6) budget 2020 - 2100 in Gt scope years temporary overshoot in Gt year emissions neutrality target year: 2030 2030 2035 2040 reference year: 1990 2019 China 235% -32% -67% -100% 159 13 0.0 2040 United States -44% -44% -75% -100% 56 11 0.0 2040 EU27 -51% -35% -52% -69% 43 15 0.0 2050 India 349% 6% -9% -24% 78 30 0.0 2066 Russia -55% -41% -82% -100% 22 12 0.0 2038 Japan -40% -38% -59% -80% 15 13 0.0 2045 Nigeria 72% 2% 0% -1% 9 74 0.0 - Tab. 9: Linear emission paths - reference values big six - B650 / P50 / NNE0 / LUC0 30 global CO2 budget 2020 - 2100 in Gt 650 minimum annual emissions 0% weighting population 0% LUC budget 2020 - 2100 in Gt 0 reference values (linear emission paths, RM-6) budget 2020 - 2100 in Gt scope years temporary overshoot in Gt year emissions neutrality target year: 2030 2030 2035 2040 reference year: 1990 2019 China 297% -19% -44% -69% 203 17 0.0 2047 United States -27% -27% -44% -61% 85 17 0.0 2052 EU27 -48% -32% -46% -59% 50 17 0.0 2055 India 267% -14% -45% -76% 44 17 0.0 2044 Russia -39% -20% -43% -67% 32 17 0.0 2048 Japan -33% -31% -45% -60% 19 17 0.0 2055 Nigeria 32% -21% -43% -65% 2 17 0.0 2049 Tab. 10: Linear emission paths - reference values big six - B650 / P0 / NNE0 / LUC0 31 Weighting the population with 50% instead of 100% would mean a higher ambition level for India, since among the six largest emitters, only India's per capita emissions in the base year 2019 are below the global average (see Tab. 2). For the other five, however, the requirements are reduced (see also Fig. 3). 30 Tab. 27 in the appendix shows by way of example the 60 highest national CO2 budgets resulting from these framework data. 31 Remark: If the population share is neglected and actual emissions were not considered for the years 2020 - 2024 (see footnote 27), grandfathering would result in the same targets for all countries. Calculation of Paris-compatible Emission Targets with the ESPM Page 17 / 42 Fig. 2 shows the emission paths for the six largest emitters with a global CO2 budget of 650 Gt and a population weighting of 50%. The figure also illustrates that if China does not reduce its emissions by 2030, it will create an ambition gap that others cannot easily fill. Fig. 2: Emission paths major emitters (RM-6-abs) – B650 / P50 / NNE0 / LUC0 32 Fig. 3 shows the course of the reference values 2030 to 2019 depending on the weighting of the population with a global CO2 budget of 650 Gt. 32 Actual emissions 2010 - 2024 (see also footnote 27). Calculation of Paris-compatible Emission Targets with the ESPM Page 18 / 42 Fig. 3: Weighting population vs. targets 2030/2019 major emitters – B650 / NNE0 / LUC0 33 Tab. 11 considers a potential for net negative emissions (and thus for an overshoot) of -25% and a LUC budget of -180 Gt. These figures are based on the illustrative model path P3 from the IPCC Special Report 2018 (cf. Wolfsteiner & Wittmann, 2025e). 34 However, relying so heavily on negative CO2 emissions harbours massive risks. 35 global CO2 budget 2020 - 2100 in Gt 650 minimum annual emissions -25% weighting population 50% LUC budget 2020 - 2100 in Gt -180 reference values (linear emission paths, RM-6) budget 2020 - 2100 in Gt scope years temporary overshoot in Gt year emissions neutrality target year: 2030 2030 2035 2040 reference year: 1990 2019 China 358% -6% -21% -36% 205 17 101.1 2062 United States -21% -21% -33% -45% 72 14 39.8 2064 EU27 -43% -26% -35% -44% 55 19 15.6 2072 India 372% 11% 1% -9% 100 39 6.8 2084 Russia -31% -10% -25% -40% 28 15 16.8 2061 Japan -28% -25% -35% -45% 19 17 7.2 2069 Nigeria 79% 7% 8% 10% 12 95 0.0 - Tab. 11: Linear emission paths - reference values big six - B650 / P50 / NNE25 / LUC180 33 Without taking actual emissions after 2019 into account, all countries would start at the same value with a population weighting of 0% (grandfathering). 34 See limitation described in footnote 10. 35 See footnote 8 and (Wolfsteiner & Wittmann, 2025e). Calculation of Paris-compatible Emission Targets with the ESPM Page 19 / 42 4.2 Exemplary global framework data reflect the NDCs of USA, EU and Japan The following exemplary combinations of the global framework data in Tab. 12 lead to results that come close to the targets in the NDCs of the USA, the EU and Japan for 2030 (see Tab. 13). Due to the limitations associated with negative CO2 emissions, conservative assumptions were made for the LUC budget and potential of net negative emissions (cf. Wolfsteiner & Wittmann, 2025e). Population weighting was used as a free parameter to map the NDCs for 2030 of the countries considered here as closely as possible. global CO2 budget 2020 - 2100 in Gt 550 minimum annual emissions -2% weighting population 15% LUC budget 2020 - 2100 in Gt 0 reference values (linear emission paths, RM-6) budget 2020 - 2100 in Gt scope years temporary overshoot in Gt year emissions neutrality target year: 2030 2030 2035 2040 reference year: 1990 2019 China 261% -26% -57% -88% 160 14 13.8 2042 United States -33% -33% -55% -77% 65 13 5.5 2046 EU27 -51% -35% -52% -68% 40 14 3.0 2050 India 287% -9% -36% -63% 46 18 2.7 2047 Russia -45% -28% -58% -89% 24 13 2.2 2042 Japan -37% -35% -53% -71% 15 13 1.2 2048 Nigeria 53% -9% -20% -31% 4 29 0.1 2072 Tab. 12: Linear emission paths - reference values big six – B550 / P15 / NNE2 / LUC0 Using the framework data from Tab. 12 and comparing the results with the countries' commitments leads to the following results (see Tab. 13): country framework data Tab. 12 NDC (see Tab. 5) deviation % points China -26% +11% -37% United States -33% -41% 8% EU27 -35% -41% 6% India -9% +18% -26% Russia -28% -8% -20% Japan -35% -36% 1% Tab. 13: Comparison with NDCs (change 2030 vs. 2019) - B550 / P15 / NNE2 / LUC0 Disregarding the fact that the countries' targets generally refer to all greenhouse gases, the framework data used for Tab. 12 are a good representation of the current targets of the EU, USA and Japan for 2030. The resulting national budgets based on the framework data in Tab. 12 also correspond to the implicit CO2 budgets for these countries based on their NDCs (see Tab. 14): Calculation of Paris-compatible Emission Targets with the ESPM Page 20 / 42 Gt national budget (Tab. 12) implicit budget36 (Tab. 6) deviation in % China 160 332 108% United States 65 73 12% EU27 40 42 4% India 46 91 98% Russia 24 45 89% Japan 15 17 13% sum 350 600 71% Tab. 14: Comparison with NDCs (budgets) - B550 / P15 / NNE2 / LUC0 However, the results for China, India and Russia are far apart. Even India and Nigeria, would have to reduce their emissions significantly by 2030, despite far below-average per capita emissions in 2019 (see Tab. 2). 37 The question arises as to whether, for example, China and India could achieve the targets for 2030 according to Tab. 12 by taking a different emissions pathway. The framework data from Tab. 12 is used below to show the entire range of plausible emission paths (see Tab. 15): 38 China global CO2 budget 2020 - 2100 in Gt 550 minimum emissions -2% weighting population 15% LUC budget in Gt 0 scenario type: RM-1-const RM-5-rad RM-3-lin RM-4-quadr RM-6-abs target year changes versus 2019 2025 -1% 12% 12% 12% 5% 2030 -44% -26% -18% -5% -26% 2035 -68% -68% -68% -74% -57% 2040 -82% -89% -94% -102% -88% 2045 -90% -97% -102% -102% -102% 2050 -94% -102% -102% -102% -102% year emissions neutrality 2061 2048 2044 2039 2042 overshoot in Gt 9.1 12.1 13.3 14.6 13.8 start change rate 2025 -10.8% 0.8% 0.8% 0.8% -5.6% national budget in Gt 160 Tab. 15: RM Scenario Types - reference values China - B550 / P15 / NNE2 / LUC0 39 In scenario type RM-4, China would only have to reduce its emissions by 5% by 2030 compared to 2019. However, this has the price that emission neutrality must then be achieved earlier and more 36 See footnote 25 for the limitations. 37 Our web app can also be used to check whether a country is on the right track: http://national-budgets.climate-calculator.info. 38 In scenario types RM 3 - 5, the rate of change for the starting year (here: 2025) can be specified on the basis of a realistic estimate. Since this rate of change is the basis for the entire course of the following rates of change, a normalised value must be used that is not influenced by temporary effects such as the pandemic. For the reference values shown here, the actual rates for 2024 was used as the starting rate of change in scenario types RM 3 - 5. In order to find a solution in the respective scenario type, this starting value may have been changed slightly. 39 Structure of the tables with the RM Scenario Types: The emission targets of scenario types RM 3 - 5 for 2030 are less ambitious from left to right. Calculation of Paris-compatible Emission Targets with the ESPM Page 21 / 42 net negative emissions must be realised. But even this scenario type is still far from China's 2030 target in its NDC (see Tab. 13). Fig. 4: RM Scenario Types – emission paths and annual change rates China – B550 / P15 / NNE2 / LUC0 40 The results for the scenario types are also shown below for the other countries analysed: United States global CO2 budget 2020 - 2100 in Gt 550 minimum emissions -2% weighting population 15% LUC budget in Gt 0 scenario type: RM-1-const RM-5-rad RM-3-lin RM-4-quadr RM-6-abs target year changes versus 2019 2025 -15% -6% -6% -7% -11% 2030 -48% -32% -25% -15% -33% 2035 -68% -63% -60% -57% -55% 2040 -80% -83% -86% -94% -77% 2045 -88% -94% -97% -102% -99% 2050 -92% -98% -102% -102% -102% year emissions neutrality 2066 2053 2048 2043 2046 overshoot in Gt 3.2 4.7 5.2 5.8 5.5 start change rate 2025 -9.2% 0.3% 0.3% 0.3% -4.7% national budget in Gt 65 Tab. 16: RM Scenario Types - reference values USA - B550 / P15 / NNE2 / LUC0 40 Actual change rates in these graphics: 2019 - 2024. Calculation of Paris-compatible Emission Targets with the ESPM Page 22 / 42 EU27 global CO2 budget 2020 - 2100 in Gt 550 minimum emissions -2% weighting population 15% LUC budget in Gt 0 scenario type: RM-1-const RM-5-rad RM-3-lin RM-4-quadr RM-6-abs target year changes versus 2019 2025 -22% -17% -17% -17% -19% 2030 -48% -37% -32% -28% -35% 2035 -65% -59% -54% -47% -52% 2040 -77% -75% -74% -74% -68% 2045 -84% -86% -88% -93% -85% 2050 -89% -93% -96% -102% -102% year emissions neutrality 2073 2062 2056 2050 2050 overshoot in Gt 1.4 2.2 2.5 3.0 3.0 start change rate 2025 -7.7% -2.0% -2.0% -2.0% -3.9% national budget in Gt 40 Tab. 17: RM Scenario Types - reference values EU - B550 / P15 / NNE2 / LUC0 Fig. 5: RM Scenario Types – emission paths and annual change rates EU – B550 / P15 / NNE2 / LUC0 India global CO2 budget 2020 - 2100 in Gt 550 minimum emissions -2% weighting population 15% LUC budget in Gt 0 scenario type: RM-1-const RM-5-rad RM-3-lin RM-4-quadr RM-6-abs target year changes versus 2019 2025 13% 29% 29% 29% 18% 2030 -28% 3% 17% 36% -9% 2035 -54% -45% -42% -45% -36% 2040 -70% -78% -85% -98% -63% 2045 -81% -93% -99% -102% -90% 2050 -88% -99% -102% -102% -102% year emissions neutrality 2072 2052 2046 2041 2047 overshoot in Gt 1.3 2.5 2.8 3.0 2.7 start change rate 2025 -8.6% 4.6% 4.6% 4.6% -4.4% national budget in Gt 46 Tab. 18: RM Scenario Types - reference values India - B550 / P15 / NNE2 / LUC0 Calculation of Paris-compatible Emission Targets with the ESPM Page 23 / 42 The target value in scenario type RM-3 for 2030 could be compatible with India's NDC (cf. Tab. 4 and Tab. 13). But in this scenario type and with the assumptions made here about the global framework data, India would have to achieve emission neutrality as early as 2046 instead of 2070 as set out in its NDC. Russia global CO2 budget 2020 - 2100 in Gt 550 minimum emissions -2% weighting population 15% LUC budget in Gt 0 scenario type: RM-1-const RM-5-rad RM-3-lin RM-4-quadr RM-6-abs target year changes versus 2019 2025 -4% 11% 11% 11% 2% 2030 -45% -26% -16% -1% -28% 2035 -69% -70% -72% -82% -58% 2040 -83% -91% -96% -102% -89% 2045 -90% -98% -102% -102% -102% 2050 -94% -102% -102% -102% -102% year emissions neutrality 2061 2047 2043 2038 2042 overshoot in Gt 1.4 2.0 2.1 2.3 2.2 start change rate 2025 -10.8% 2.9% 3.0% 3.0% -5.6% national budget in Gt 24 Tab. 19: RM Scenario Types - reference values Russia - B550 / P15 / NNE2 / LUC0 Japan global CO2 budget 2020 - 2100 in Gt 550 minimum emissions -2% weighting population 15% LUC budget in Gt 0 scenario type: RM-1-const RM-5-rad RM-3-lin RM-4-quadr RM-6-abs target year changes versus 2019 2025 -21% -16% -16% -16% -17% 2030 -48% -39% -35% -30% -35% 2035 -66% -61% -57% -51% -53% 2040 -78% -77% -77% -76% -71% 2045 -86% -88% -89% -93% -89% 2050 -91% -94% -96% -101% -102% year emissions neutrality 2071 2061 2056 2050 2048 overshoot in Gt 0.6 0.9 1.0 1.1 1.2 start change rate 2025 -8.2% -3.0% -3.0% -3.0% -4.2% national budget in Gt 15 Tab. 20: RM Scenario Types - reference values Japan - B550 / P15 / NNE2 / LUC0 Calculation of Paris-compatible Emission Targets with the ESPM Page 24 / 42 Nigeria global CO2 budget 2020 - 2100 in Gt 550 minimum emissions -2% weighting population 15% LUC budget in Gt 0 scenario type: RM-1-const RM-5-rad RM-3-lin RM-4-quadr RM-6-abs target year changes versus 2019 2025 1% 10% 10% 10% 2% 2030 -18% 13% 24% 34% -9% 2035 -32% -2% 15% 38% -20% 2040 -45% -24% -12% 2% -31% 2045 -55% -46% -46% -56% -42% 2050 -63% -65% -73% -92% -53% year emissions neutrality 2097 2076 2064 2054 2072 overshoot in Gt 0.0 0.1 0.1 0.1 0.1 start change rate 2025 -3.9% 4.8% 4.8% 4.8% -2.1% national budget in Gt 4 Tab. 21: RM Scenario Types - reference values Nigeria - B550 / P15 / NNE2 / LUC0 Fig. 6: RM Scenario Types – emission paths and annual change rates Nigeria – B550 / P15 / NNE2 / LUC0 Calculation of Paris-compatible Emission Targets with the ESPM Page 25 / 42 Fig. 7: Emission paths major emitters (RM-3-lin) – B550 / P15 / NNE2 / LUC0 4.3 Exemplary global framework data reflect the NDCs of China and India In order to obtain targets for China and India that move in the direction of their NDCs, the global budget, the LUC budget and the potential for net negative emissions would each have to be changed in a direction and to an extent that would significantly increase the risk of not successfully limiting global warming (see Tab. 22 and Tab. 23). In particular, the risks of such a massive negative LUC budget and such a high potential for net negative emissions are hardly acceptable. 41 On the other hand, there would then be a scope for the EU and Japan to provide budgets to India and China. For example, with the framework data from Tab. 12, the EU would receive a budget of around 40 Gt; in Tab. 24 it would be around 61 Gt. However, due to the small share of the EU and Japan in global emissions, the resulting scope is small. 41 See footnote 8 and (Wolfsteiner & Wittmann, 2025e). Calculation of Paris-compatible Emission Targets with the ESPM Page 32 / 42 German Federal Constitutional Court on CO2 budgets Excerpt from the main considerations of the Federal Constitutional Court (BVerfG, 2021): “The constitutionally relevant temperature threshold of well below 2°C and preferably 1.5°C can in principle be converted into a global CO2 residual budget, which can then be distributed among the states. The Intergovernmental Panel on Climate Change (IPCC) has named concrete global CO2 residual budgets for various temperature thresholds and various probabilities of occurrence on the basis of a quality-assurance procedure, disclosing the remaining uncertainty. On this basis, the German Advisory Council on the Environment [ (SRU, 2020)], note by the authors] has also determined a concrete national residual budget for Germany from 2020 that would be compatible with the Paris target. Due to the uncertainties and evaluations contained therein, the budget size determined cannot currently provide a numerically accurate measure for constitutional court review. The legislature still has room for manoeuvre. However, it may not fill this space at its political discretion. If there is scientific uncertainty about environmentally relevant causal relationships, Article 20a of the Basic Law imposes a special duty of care on the legislature. According to this, already reliable indications of the possibility of serious or irreversible impairments must be taken into account. At present, a violation of this duty of care cannot be established. It follows that estimates by the IPCC on the size of the remaining global CO2 residual budget must be taken into account, even though they contain uncertainties. The emission levels regulated in Article 4 para. 1 sentence 3 KSG [Climate Protection Act, note by the authors] in conjunction with Annex 2 would largely exhaust the residual budget determined by the German Advisory Council on the Environment on the basis of the IPCC estimates until the year 2030. However, compared to the uncertainties currently included in the calculation of the residual budget, the degree of shortfall did not form a sufficient basis for a constitutional court challenge.” Excursus 1: German Federal Constitutional Court on CO2 budgets German Federal Constitutional Court on freedom opportunities for future generations Excerpt from the guiding principles of the decision of the Federal Constitutional Court (BVerfG, 2021): “Under certain conditions, the Basic Law obliges the safeguarding of freedom protected by fundamental rights over time and the proportionate distribution of opportunities for freedom over the generations. In terms of subjective law, fundamental rights, as an intertemporal safeguard of freedom, protect against a unilateral shifting of the greenhouse gas reduction burden imposed by Article 20a GG [Basic Law, note by the authors] to the future. The objective-law protection mandate of Article 20a of the Basic Law also includes the necessity to treat the natural foundations of life with such care and to leave them to posterity in such a condition that future generations could not continue to preserve them only at the price of radical abstinence of their own. The protection of future freedom also requires that the transition to climate neutrality be initiated in good time. In concrete terms, this requires the early formulation of transparent targets for further greenhouse gas reductions that provide orientation for the necessary development and implementation processes and give them a sufficient degree of development pressure and planning certainty.” Excursus 2: German Federal Constitutional Court on freedom opportunities for future generations Calculation of Paris-compatible Emission Targets with the ESPM Page 33 / 42 Allocation of a global CO2 budget The global community has set itself the following framework: “Acknowledging that the global nature of climate change calls for the widest possible cooperation by all countries and their participation in an effective and appropriate international response, in accordance with their common but differentiated responsibilities and respective capabilities and their social and economic conditions.” United Nations Climate Change Framework Convention of 1992 Five basic allocation approaches can be distinguished:48 (1) Grandfathering (2) Equality (3) Responsibility (4) Capability (5) Cost efficiency Fig. 10: Allocation principles for the distribution of a remaining global CO2 budget49 48 See (Dekker, et al., 2025) for a comprehensive classification of effort-sharing approaches and an assessment of their influence on national targets under different equity, strategic, and scientific assumptions. See also: (Robiou du Pont, et al., 2017, p. 40; Robiou du Pont, et al., 2025). 49 „Allocation and fairness principles (corners of the pentagon, in black) and methods to quantify these principles or combinations thereof (in coloured or grey text boxes)” (Dekker, et al., 2025, Supplementary information). Source of the figure: (Dekker, et al., 2025, Supplementary information: Figure SI.3). Original figure concept based on (Höhne, et al., 2014). In the field labelled ‘Per capita convergence’, ‘or Weighting’ has been added to reflect the approach used in this paper. Calculation of Paris-compatible Emission Targets with the ESPM Page 34 / 42 In addition to the allocation keys "current emissions share" (1) and "current population share" (2) used here, other criteria may therefore be taken into account such as historical emissions (3) or GDP per capita (4). Including historical emissions highlights the responsibility of the "old" industrialised countries for the decarbonisation process, but results in unrealistic territorial emission targets. However, historical emissions could play a significant role, especially in compensating for Loss and Damage. The idea behind "capability" is that wealthier countries should set themselves more ambitious goals. Since there is a correlation between emissions per capita and GDP per capita for the six largest emitters (cf. Tab. 26), the GDP per capita criterion is already indirectly mapped via the weighting of the population. However, the correlation coefficient of 0.7 is clearly below 1, so that this mapping is not perfect. In principle, it might make more sense to use criteria based on economic performance for direct financial issues such as contributions to Climate Finance. correlation per capita emissions in t GDP in TUSD India 2 7 EU27 7 45 China 8 16 Japan 9 41 Russia 13 28 United States 15 62 correlation coefficient 0.68 Tab. 26: GDP per capita of the six largest emitters Instead of allocating a global budget, a global path can be allocated by using a convergence model [also a combination of the approaches (1) and (2)] (cf. Sargl, et al., 2024a). Using a convergence model implies an implicit weighting of the population that is the same for all countries (cf. Wittmann & Wolfsteiner, 2023). In the Regensburg Model convergence approach, this implicit weighting is around 12% with a linear emission path and a per capita emissions convergence at 0.5 t (cf. Wolfsteiner & Wittmann, 2024b; Sargl, et al., 2024b). Due to its characteristics, the Regensburg Model can be described as a kind of "moral floor" for the industrialised countries. Another approach (5) are Integrated Assessment Models (IAMs), which can be used to identify globally cost-efficient national emission paths (cf. van Soest, et al., 2021).50 But the results of IAMs are a "black box" for policy makers. For the ESPM approach, on the other hand, only a few framework data need to be specified politically and equity aspects can be explicitly considered. This means that emissions paths can ultimately be determined politically in a transparent manner in the ESPM, taking socio-economic factors into account. In convergence models and IAMs, the national budgets and thus the distribution of a global CO2 budget result indirectly. A distinction can be made whether the allocation of a global CO2 budget refers to the actual territorial emissions of a country or to tradable emission rights. If allocation is based on emission rights, the scope for climate justice can be considered even greater (Rajamani, et al., 2021; Robiou du Pont, et al., 2025). However, it is important to keep in mind that the resulting potential financial flows in a subsequent emissions trading should be realistic. The potential to generate certificates with different weightings of the population is discussed in Excursus 4. 50 For a recent approach that derives nationally consistent emission targets from global welfare-optimizing IAM scenarios, see (van der Wijst, et al., 2025). Calculation of Paris-compatible Emission Targets with the ESPM Page 35 / 42 If the allocation is based on territorial emissions, it would have to be examined whether it makes sense for countries with low per capita emissions today to build up an economy that is more fossil fuel-based and has to decarbonise again soon afterwards. When allocating a global CO2 budget, it should be taken into account that it must also work for countries with currently high per capita emissions or high per capita incomes. There are two aspects to consider: Territorial emission targets or payments within the framework of global emission trading (1) must also be politically enforceable at national level. (2) should also be economically viable in the sense that the global economy is not unduly affected. This would otherwise also have a considerable negative impact on countries with low economic power. An ethical justification for these aspects can be found in Rawls' "Theory of Justice". Excursus 3: Allocation of a global CO2 budget Calculation of Paris-compatible Emission Targets with the ESPM Page 36 / 42 Potential for emissions trading between countries The exemplary national CO2 budgets in Tab. 27 in the appendix, which are derived from various global framework data, show that: • The lower the weighting of the population, the smaller the scope for newly industrialising and developing countries to generate certificates within the framework Article 6 (2) of the Paris Agreement. The stated scopes of the national budgets can serve as a measure of this leeway. • A higher the weighting of the population, would result in a higher demand for certificates of the industrialised countries plus China. • Ambitious targets, for example those of the EU, only allow limited scope for compensating for the lack of ambition of emerging countries such as China and India. Emissions trading therefore does not solve the fundamental problem of a tight global CO2 budget. For a further development of the Cooperative Mechanisms under Article 6 of the Paris Agreement with regard to a global remaining CO2 budget, it would make sense that the NDCs must state the CO2 budget that a country will claim for itself through the NDC in the future. Such explicit national CO2 budgets could also facilitate emissions trading between countries, especially if the NDCs are Paris-compatible in sum. However, the integrity of emissions trading on this basis is undermined if NDCs are not met. Excursus 4: Potential for emissions trading between countries Calculation of Paris-compatible Emission Targets with the ESPM Page 37 / 42 Regensburg Model Scenario Types From an overall perspective of climate policy, scenarios with a nonlinear emissions path may be useful. Additional scenario types also offer the possibility of taking country-specific features into account. The Regensburg Model Scenario Types RM 1 - 5 are based on the course of the annual change rates. Annual rates of change are used in many areas and are particularly suitable for describing a meaningful course of emission paths. Four basic types can be distinguished in a monotonically decreasing progression of the annual rates of change: (1) Constant: constant annual reduction rates (RM-1, straight line) (2) Linear: linearly monotonically decreasing (RM-3; straight line) (3) Concave: initially under-proportional monotonically decreasing (RM-2, RM-4) (4) Convex: initially over-proportional monotonically decreasing (RM-5) In addition, the scenario type RM-6 uses linear emission paths. Accordingly, the annual reduction rates for RM-6 have a concave course and the annual reduction amount is constant. With our web app http://paths.climate-calculator.info the different scenario types can be graphically traced (see also Fig. 1and e.g. Fig. 4). For a comprehensive mathematical description, we refer to: (Wolfsteiner & Wittmann, 2024a). The advantage of scenario types RM 3 - 5 is that the start change rate can be specified on the basis of the real circumstances and that increasing emissions can also be mapped by specifying a positive start change rate. The following questions should be considered, when assessing a scenario type: (1) Which annual change rates are when realistic? (2) Does an initially slowly rising level of ambition (RM-2/4 and RM-6) imply an unjustifiable burden for the future, since this later implies very high reduction rates? (3) Do high later reduction rates make sense, if they provide a longer lead time for the necessary investments and the investments could then rather be made within the framework of normal investment cycles? However, this requires a very credible climate policy backed by effective instruments. (4) Does an initially rapidly rising level of ambition (RM-3 and RM-5) convey a more credible climate protection policy that creates planning security for public and private investments in a fossil-free future? The German Advisory Council on the Environment (SRU) recommends to refrain from linear emission paths (RM-6): "A slow start, hoping for steep emission reductions in later years, jeopardises compliance with the budget and climate targets" (SRU, 2020, p. 56). This argument would also apply to the scenario types RM-2 and RM-4. The decision of the German Federal Constitutional Court on the Climate Protection Act also implicitly poses the question of what annual change rates we must accept today so that the freedom of future generations is not unduly restricted (see Excursus 2: German Federal Constitutional Court on freedom opportunities for future generations). To avoid very high annual reduction rates in later years, the scenario types RM-3 and RM-5 are suitable. 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