Carbon dioxide removal deployment consistent with global climate objectives

doi:10.21203/rs.3.rs-3719978/v1

The IPCC 6th Assessment Report lacked sufficient land sector scenario information to estimate total carbon dioxide removal (CDR) deployment. Using a new dataset, we show that land CDR plays an important near-term role and novel removal technologies scale to multi-gigatonne levels by 2050 and beyond to balance residual emissions and draw down warming. Reducing fossil fuel and deforestation emissions accounts for over 80% of net greenhouse gas reductions until global net zero CO2 independent of climate objective stringency.

Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation

Earth and environmental sciences/Climate sciences/Climate change/Projection and prediction

The Intergovernmental Panel on Climate Change (IPCC) assesses Integrated Assessment Model (IAM) scenarios to explore different ways to meet global climate targets and inform international and national climate policy processes¹. Climate mitigation is achieved through deep cuts in gross CO₂ and non-CO₂ emissions as well as different methods of carbon dioxide removal (CDR) depending on assumptions of the availability, cost and feasibility of different mitigation options^2,3. However, the IPCC’s 6th Assessment Report (AR6) did not provide a complete assessment of total CDR deployment, and consequently, residual CO₂ and greenhouse gas (GHG) emissions in the assessed scenarios. This was because the underlying modelling frameworks either used different reporting methodologies for land CDR or did not separate gross emissions and removals in the land sector⁴. Scientific publications that analyse removals based on the AR6 scenarios either omit scenarios that do not report land removals⁵ (without accounting for differences in reporting methodologies) or use net-negative CO₂ emissions from the agriculture, forestry and land-use (AFOLU) sector as a proxy for land-based removals⁶ (ignoring current removals and near-term land sector dynamics). This creates a fundamental data and knowledge gap, as a comprehensive understanding of the mitigation solution space requires information on both gross emissions reductions and total removals to evaluate the relevant contributions and trade-offs of different mitigation options.

Here, we close this gap by providing the first comprehensive global and regional assessment of total CDR in mitigation scenarios using a novel dataset of land-based carbon fluxes⁷ derived from the AR6 scenario database⁸. We evaluate the roles of gross emission cuts and resulting residual emissions as well as total CDR across three categories of pathways assessed by the IPCC - C1 (no or limited overshoot 1.5°C), C2 (high overshoot 1.5°C) and C3 (>67% below 2°C) pathways (see Methods for definitions). We further evaluate the components of total CDR across two categories - conventional CDR on land (methods that provide CDR at scale today, capturing and storing carbon in the land biosphere) and novel CDR (proposed methods not used at scale today that store captured carbon in geological formations, ocean, or products)⁹.

We assess the different greenhouse gas emissions (GHG) emission reduction rates over different time frames across the three IPCC categories of pathways (Table 1). In 1.5°C pathways (C1), most of the mitigation between 2020 and 2030 (Figure 1a) is achieved through reducing gross CO₂ emissions (70% [64, 77 interquartile range]) and cutting non-CO₂ emissions (20% [16, 24]). This is accompanied by a smaller, yet important, contribution from pursuing sustainable land-use strategies through halting deforestation and expanding conventional CDR on land (accounting for 10% [5, 14] of net GHG reductions), nearly doubling the volume of CDR in this decade (Table 1). Across most scenarios, novel CDR methods scale up by mid-century to support the achievement of net zero CO₂, increasing to levels of around 4 Gt CO₂ [2, 6] by 2050. Between 2020 and global net zero CO₂, gross CO₂ reductions account for 71% [66, 74] of the net GHG reductions in C1 pathways with CDR contributing a much smaller amount (15% [12, 21]). These patterns (dominant reductions in gross CO₂ emissions and alternating importance of non-CO₂ reductions and CDR) are similar in C2 and C3 pathways (Figure SI1 and Table SI1) but with slower near-term net GHG reductions (Table 1). However, across all the categories of pathways, over 80% of the net GHG reductions between 2020 and global net zero CO₂ are achieved by cuts in gross CO₂ and non-CO₂ emissions (Figure 1c). This indicates that less stringent climate objectives do not imply a fundamental change in the scale of gross CO₂ reductions necessary, but merely shift this over time, raising questions of intergenerational fairness. In other words, overall mitigation effort is similar across different temperature categories, while climate impacts and related adaptation needs increase in line with additional warming.

Delaying mitigation action impacts the volume and composition of CDR until global net zero CO₂(Figure 1d and 1e). We conceptualise delay across two dimensions - the time to halve net CO₂ emissions and the number of years until global net zero CO₂ is achieved. We find that the amount of conventional CDR on land is largely consistent across different timings of delayed emissions reductions, implying that scenarios utilise land-based CDR regardless of the delay of emissions reductions elsewhere. Conversely, we observe a strong signal both in the median and extreme values in the amount of novel CDR utilised in scenarios which have longer net emission halving times, showing scenarios’ dependence on future, unproven CDR technologies when net emissions reductions are delayed. Delaying the time of net zero CO₂ results in an increase in the total CDR deployed till this year; for scenarios with a net zero timing by mid-century, the total volume of CDR deployed is 166 Gt CO₂ [149, 193], increasing to 251 Gt CO₂ [203, 320] and 445 Gt CO₂ [345, 524] respectively for scenarios with a net zero timings between 2050 and 2075, and later than 2075. Conventional CDR on land tends to increase faster in scenarios with net zero CO₂ timing between 2050 and 2075 (Figure 1d) while novel CDR increases faster in scenarios with net zero CO₂ timing between 2075 and 2100 (Figure 1e). This reflects the lead time necessary to scale up novel removals, which are still at a nascent stage of development¹⁰.

Beyond global net zero CO₂ CDR is the dominant mitigation option used in scenarios. CDR volumes are over 3 times higher than the 2020 levels in C1 pathways and over 6 and 4 times higher in C2 and C3 pathways by 2100 (Table 1). Two factors influence the volume of deployed CDR - the cumulative residual CO₂ emissions that need to be balanced to stabilise warming (see identity line in Figure 1f) and the desired post-peak cooling. The latter is influenced by the residual non-CO₂ emissions. In the assessed C1 scenarios, 55% [44,91] (in volume terms, 342 Gt CO₂ [245, 426]) of the total CDR deployed over this timeframe is to balance residual gross CO₂ emissions. The corresponding values for C2 scenarios are somewhat lower at 50% [40, 60] (in volume terms, 298 Gt CO2 [236, 384]) linked to a greater demand for CDR to reverse temperature overshoot in C2 pathways when compared to C1 pathways - higher volumes of CDR are deployed in C2 pathways to reverse warming (309 Gt CO₂ [221, 424]) when compared to the C1 pathways (184 Gt CO₂ [26, 418]). In terms of composition, novel CDR accounts for around two thirds of total CDR between net zero CO₂ and 2100 (66% [58, 79]) across all pathways with similar ranges for each category of pathway.

Table 1: Key global benchmarks in assessed mitigation pathways. Note that we use the modelled 2020 values from the scenarios. We report the median and the interquartile range across the scenarios.

Category

Variable

Level [Gt CO₂/ yr]

2020

2030

2035

2050

2100

C1

(n=70)

Net GHG

(direct)

53.4

[55.2, 52.6]

28.9

[32.4, 26.0]

21.1

[24.2, 18.5]

7.2

[8.7, 5.3]

1.7

[7.6, -5.9]

Gross CO₂

(direct)

41.8

[43.7, 40.0)

24.5

[26.2, 21.1]

18.1

[20.6, 16.1]

8.3

[10.1, 7.5]

5.5

[11.7, 3.9]

Non-CO₂

14.8

[15.2, 14.0]

9.8

[10.8, 9.3]

9.0

[9.9, 8.4]

7.6

[8.9, 6.7]

6.6

[7.6, 5.3]

CDR

(direct)

2.5

[2.5, 2.5]

5.1

[5.7, 3.9]

6.1

[7.1, 4.9]

9.3

[11.5, 7.6]

11.8

[17.1, 9.5]

C2

(n=102)

Net GHG

(direct)

55.2

[55.7, 53.4]

41.5

[49.0, 36.0]

31.4

[36.4, 27.9]

12.8

[15.5, 9.0)

-5.5

[-2.7, -8.0]

Gross CO₂

(direct)

43.3

[43.9, 41.5]

33.5

[39.2, 28.4]

26.2

[29.3, 22.5]

12.6

[16.1, 10.7]

5.3

[7.9, 4.0]

Non-CO₂

14.3

[15.2, 13.8]

11.8

[13.4, 10.6]

10.0

[11.0, 9.4]

8.2

[9.1, 7.7]

6.0

[7.1, 4.9]

CDR

(direct)

2.5

[2.5, 2.5]

3.2

[4.1, 2.8]

4.5

[5.6, 3.5]

8.1

[10.5, 6.5]

17.6

[19.9, 13.9]

C3

(n=229)

Net GHG

(direct)

53.5

[55.5, 52.5]

43.1

[49.1, 37.9]

34.5

[37.6, 29.5]

18.5

[21.1, 14.1]

3.8

[8.1, -2.1]

Gross CO₂

(direct)

42.1

[43.7, 40.0]

34.0

[39.3, 30.8]

28.1

[30.3, 24.8]

16.2

[18.3, 13.8]

8.7

[12.7, 6.8]

Non-CO₂

14.8

[15.3, 14.0]

12.2

[13.2, 11.0]

10.5

[11.4, 9.3]

8.6

[9.1, 7.2]

6.8

[7.7, 5.4]

CDR

(direct)

2.5

[2.5, 2.5]

3.2

[4.7, 2.7]

4.1

[5.5, 3.2]

6.3

[9.4, 5.5]

13.5

[17.4, 10.1]

The composition of CDR and gross emission reductions vary across world regions depending on the cost-effective allocations in each scenario we assess, and we find some consistent regional observations and trends across scenarios (Supplementary Table 2). Cost-effective allocations reflect approaches which find the lowest cost deployment of mitigation options across regions which often differ quite significantly from the responsibility for deploying the resources to support this mitigation accounting for foundational principles of the Paris Agreement, including the principle of equity and common but differentiated responsibilities and respective capabilities^11,12.

For the Asia region, we note a dominant contribution (median of around 80%) from gross CO₂ emission reductions across all three time periods in the C1 pathways with the balance largely coming from non-CO₂ reductions followed by CDR. However, in C2 and C3 pathways where there is slower global near-term action, CDR plays a larger role beyond 2050, accounting for over 20% (median) of the regional net GHG reductions. For the OECD and EU region we find similar patterns between 2020 and 2030 and onwards to 2050; however, after this 2050 removals play a much larger role in net GHG reductions across each category of pathways accounting for a median of around 43%, 48%, 35% respectively across the C1, C2 and C3 pathways. For the Latin America region, our analysis indicates that relatively high shares of GHG reduction (compared to other regions) are met through CDR between 2020 and 2030, with this role growing in each time frame thereafter. In C1 pathways, CDR accounts for 18% [14, 28.5] of regional GHG cuts between 2020 and 2030, and 32% [22, 42] and 79.5% [49, 136] between 2030 and 2050, and 2050 and 2100 respectively. A value greater than 100% for the 75th percentile in the latter estimate indicates that one (or both) of the other two components (gross CO₂ or non-CO₂ emissions) are growing in this period and hence have a “negative” contribution.

Broader sustainability concerns will play a role in constraining the role of CDR beyond the influence of regional costs and potentials. For some novel carbon removal options like bioenergy with carbon capture and storage (BECCS), these sustainability concerns include competition for land (and impact on food prices) and impacts on biodiversity, among others¹². Scenarios with relatively more sustainable levels of global bioenergy demand at net zero CO₂ (see Methods) tend to show a slight increase in deployment of conventional CDR on land across all world regions, with a marked decrease in the deployment of novel CDR between 2020 and global net zero CO₂ (Figure 2). Large-scale deployment of conventional CDR on land is associated with a different set of concerns, including the impact on local livelihoods¹³ and the potential effects of climate-related feedbacks on the integrity of the sinks. This points to the need for a balanced portfolio approach to CDR deployment in mitigation pathways with an aim to balance regional equity and sustainability trade-offs moving away from a simplistic treatment of CDR as technologies with a “negative” emission sign.

In this paper, we have provided the first comprehensive assessment of gross reductions and CDR in the AR6 mitigation scenarios using a dataset that separates net emissions in the land-use sector into its components. We show that over 80% of the net GHG cuts between 2020 and global net zero CO₂ are achieved via deep cuts in current sources of emissions. Conventional CDR on land plays an important near-term role, scaling up quickly from present levels in future pathways, largely in Latin America and Asia. Our results are aligned with model-based land-use, land-use change and forestry accounting conventions, and results may differ when using accounting conventions by parties to the UNFCCC, highlighting the importance of translating between both conventions⁷. A limitation of the current scenario literature is the lack of a comprehensive representation of climate-related feedbacks and risks (sink strength, droughts and wildfires) which could strongly reduce land-based CDR potentials¹⁴. In the medium- and long-term, novel CDR plays a more important role in future mitigation pathways. These novel CDR options, which include bioenergy with CCS, direct air capture with CCS, and enhanced weathering, among others, are currently at a nascent stage of development, expensive, and not deployed at scale¹⁵. These methods tend to be deployed across regions very differently than conventional CDR on land, but still result in large shares of CDR being deployed in currently developing regions. These relatively high contributions from developing regions raises questions around fairness given uneven distribution of responsibility for causing climate change¹⁶. Addressing these challenges will require a significant scaling up of mitigation investments, and one solution that has been suggested to address this problem is to assess fair shares of mitigation investment in these pathways¹¹, which should also take into account principles underlying the Paris Agreement, including sustainable development and equity¹⁷.

In this analysis, we use a combination of two datasets: the AR6 scenarios database and a new reanalysis dataset that estimates gross carbon dioxide removal in the land-sector⁷. This dataset is generated by reanalysing the land-components of the AR6 scenarios using the compact Earth system model OSCAR v3.2¹⁸. This dataset is available only at the R5 region level assessed by the IPCC due to land-cover data availability in the original scenarios. While the IPCC regional definitions (outlined below) are relatively coarse, they still allow us to tease out broad regional differences¹⁹. Nonetheless, they should be interpreted with caution if they are applied to component countries of these regions.

R5OECD90+EU: North America, Europe, Australia, Japan and New Zealand
R5REF: Eastern Europe and West-Central Asia
R5ASIA: Eastern Asia, Southern Asia, South-East Asia and Pacific (referred to as Asia in the main text)
R5MAF: Middle East and Africa
R5LAM: Latin America and Caribbean

We first calculate the total CDR deployed for each scenario, both at the global and the R5 region level as the sum of the novel CDR (variable label: AR6 Reanalysis|OSCARv3.2|Carbon Removal|Non-Land) and the direct conventional CDR on land (variable label: AR6 Reanalysis|OSCARv3.2|Carbon Removal|Land|Direct). This allows us to estimate the gross CO₂ emissions (which we also refer to as residual CO₂ emissions) by adding the derived total CDR to the direct net CO₂ emissions (variable label: AR6 Reanalysis|OSCARv3.2|Emissions|CO2|Direct Only). We then check whether the value for the “World” region is positive in all years and omit 6 scenarios where this is not the case. We assess the non-CO₂ contribution by subtracting the direct net CO₂ emissions from the assessed direct Kyoto greenhouse gas emissions (AR6 Reanalysis|OSCARv3.2|Emissions|Kyoto Gases|Direct Only). The constituent greenhouse gases are aggregated by converting them into CO₂-equivalent units using 100-year global warming potentials (GWP100) from the Working Group 1 contribution to the IPCC’s 6th Assessment Report²⁰. Where we refer to the global net zero CO₂ year in this analysis, we are referring to the harmonised global net zero CO₂ year reported in the metadata that accompanies the AR6 scenario database (column name: 'Year of netzero CO2 emissions (Harm-Infilled) table'). The net zero CO₂ years in the reanalysed dataset are very close to the reported harmonised global net zero CO₂ year, with a median difference of 1 year [-1, 5].

We assess three IPCC categories of scenarios in this paper²¹. The lowest is the C1 category of scenarios which limit peak warming below 1.5°C with at least a 33% chance and subsequently limit warming in 2100 below 1.5°C with at least a 50% chance. This category of pathways is aligned most closely with pathway criteria that have been suggested to operationalise the climate objectives in the Paris Agreement⁶. We also assess the C2 (limit peak warming below 1.5°C with less than a 33% chance and subsequently limit warming in 2100 below 1.5°C with at least a 50% chance) and C3 (limit peak warming below 2°C with at least a 67% chance) scenarios.

To compute the components of mitigation effort for a given period, we first calculate the change in the desired variable relative to the starting year and divide the corresponding values from the component regional results or component variables to derive the percentage compositions. We then group scenarios into three bins according to the global demand for bioenergy at the year of global net zero CO₂ (variable: Primary Energy|Bioenergy). The first bin (0-100 EJ/yr) includes scenarios with global bioenergy demand within sustainability limits previously discussed in the literature^13,22, with the other two bins (100-200 and 200+ EJ/yr) reflecting much higher levels of global bioenergy demand.

Data availability

The reanalysis dataset from ref.⁷ is available at: https://data.ece.iiasa.ac.at/genie. The AR6 scenario data from ref.^4,8 is available at: https://data.ene.iiasa.ac.at/ar6.

Code availability

The code underlying this study is openly available at: https://github.com/gaurav-ganti/2023_ganti_ar6_cdr_assessment

Author contributions

MJG conceived the research. GG and MJG performed the research and wrote the manuscript with input from all authors.

Acknowledgements

GG acknowledges support from the Bundesministerium für Bildung und Forschung (BMBF) under grant no. 01LS2108D (CDR PoEt). MJG, JCM and WFL acknowledge support by the European Research Council (ERC) under the European Union’s Horizon 2020 Framework Programme as part of the project “GeoEngineering and NegatIve Emissions pathways in Europe” (GENIE) [grant agreement No. 951542]. TG was also supported by the European Union’s Horizon Europe research and innovation program under grant agreement no. 101056939 (RESCUE project). CFS acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 101003687 (PROVIDE).

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There is NO Competing Interest.

2023ganticarbondioxideremovalar6SUPPLEMENT.docx

Carbon dioxide removal deployment consistent with global climate objectives

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