key: cord-0620073-jk9bhejp
authors: Moallemi, Enayat A.; Eker, Sibel; Gao, Lei; Hadjikakou, Michalis; Kwakkel, Jan; Reed, Patrick M.; Obersteiner, Michael; Bryan, Brett A.
title: Global pathways to sustainable development to 2030 and beyond
date: 2020-12-08
journal: nan
DOI: nan
sha: 93918fe15c8edb3345edccdc2009d4a42d633715
doc_id: 620073
cord_uid: jk9bhejp

Progress to-date towards the ambitious global 2030 agenda for sustainable development has been limited, and upheaval from the COVID-19 pandemic will further exacerbate the already significant challenges to Sustainable Development Goal (SDG) achievement. Here, we undertake a model-based global integrated assessment to characterise alternative pathways towards 36 time-bound, science-driven targets by 2030, 2050, and 2100. We show that it will be unlikely to jointly achieve socioeconomic and environmental targets by 2030, even under the most optimistic pathways and the least ambitious targets. Nonetheless, humanity can still avoid destabilisation of the Earth system and increase socioeconomic prosperity post-2030 via a Green Recovery pathway. A Green Recovery by mid- and end of the century requires reducing global population by 5% and 26%, empowering sustainable economic development by 32% and 52%, increasing education availability by 10% and 40%, reducing the total global fossil energy production by 36% and 80%, reducing agricultural land area by 7% and 10%, and promoting healthy and sustainable lifestyles by lowering consumption of animal-based foods (i.e., meat and dairy) by 39% and 50%, compared to the business-as-usual trajectories for 2050 and 2100, respectively. Our results show that the combination of these changes together towards extended, more ambitious goals by 2050 and 2100 is central to the transformative change needed to ensure that both people and planet prosper in medium- and long-term futures.

Progress to-date towards the 17 Sustainable Development Goals (SDGs) 1 , which embody the shared aspirations of humanity to promote societal welfare within the planetary boundaries 8 , has been very limited 9, 10 . With less than 10 years to go, much work is still to be done to reach these ambitious global goals.

The global COVID-19 pandemic has also disrupted national social, health, and economic systems, and shortterm recovery efforts will likely dominate the global agenda over the next decade, diverting investment and distracting nations from the longer-term multi-pronged focus required to meet the SDGs. But failing to achieve the global sustainability agenda is not an option, and calls have been made to reset it in light of the pandemic 4, 5 .

A recent evaluation of the Convention of Biological Diversity 2020 Aichi targets has shown that none have been fully achieved 11 , which has necessitated rethinking the process, and a new round of revision and targetsetting 12 . To avoid a similar outcome for the SDGs and subsequent loss of momentum in progress towards global sustainability, it is prudent to explore alternate pathways towards increasingly ambitious mediumand long-term goals to enable missed 2030 targets to be met later on, to ensure that earlier achievements are not lost through complacency, and to establish a long-term process of continuous improvement. Here, we use integrated assessment modelling to assess the performance of alternative pathways towards 36 sustainability targets under eight SDGs by 2030 (short-term) and their extensions to 2050 (medium-term) and 2100 (long-term) with increasing levels of ambition. Given current and future socioeconomic and environmental uncertainties, this assessment is timely to illuminate robust options for humanity to achieve global sustainability aspirations over the course of the 21 st century, even if we fail to fully achieve the United Nations (UN) 2030 Agenda.

The scientific community has attempted to inform policy discussion on the SDGs with model-based scenario assessments, but mostly with a focus on specific sectors such as land 13 , food 14, 15 , energy 16, 17 , and biodiversity conservation 18 with a few notable exceptions of global nexus-type assessments such as food-energy-water 19 , land-food 20 , and land-food-biodiversity 21 . The few, more comprehensive, integrated assessments of global sustainability that do exist have either used relatively simple models that do not capture the interactions of complex systems 22 , or have not assessed progress towards explicit targets consistent with the SDGs 23 . This has impeded a comprehensive understanding of progress under the uncertainty of global change and precluded a detailed characterisation of the transformative change needed to reach the sustainability targets, especially over timeframes extending well beyond 2030.

We used the Functional Enviro-economic Linkages Integrated neXus (FeliX) model 17 , a global integrated assessment model based on system dynamics 24 , to evaluate how interlinked future drivers might unfold through the nexus of population, education, economy, energy, land, food, biodiversity, and climate systems (Extended Data Figure 1 ). We explored a set of five internally consistent descriptions of future pathways aligned with the Shared Socioeconomic Pathways (SSPs) scenarios 25,26 which span a range of possibilities from continuation of current trends (business-as-usual) to implementation of very strong sustainability interventions across the economic, education, food, and energy sectors (Extended Data Table 1 and Methods).

Our SSP-compliant pathways include 'Green Recovery' representing inclusive socioeconomic and environmental development (SSP1), 'Business As Usual' as the continuation of current global average trajectories (SSP2), 'Fragmented World' characterised by regional rivalry rather than global cooperation (SSP3), a world of high 'Inequality' in human and economic opportunities (SSP4), and 'Fossil-Fuelled Development' with prospering socioeconomic yet unsustainable environmental outlook (SSP5). Green

Recovery and Fragmented World are indicative of an optimistic and pessimistic post-pandemic future. The former represents 'a new world of opportunities' where the world shows solidarity in a long-term, sustainable recovery from COVID-19 and emerges fairer, more inclusive, and more prosperous than before.

The latter represents increasingly nationalistic attitudes amplifying perceived threats, failures, and a limited capacity to build resilience for coping with future global shocks. Given the deep uncertainties inherent in the characterisation of these five pathways, we used an exploratory ensemble modelling approach 27,28 (50, Figure 1a ), the world is on track (in >50% of 50,000 realisations) for only 5 out of the 36 moderate targets, mostly related to socioeconomic SDGs. Worse, the world is stagnating or even regressing compared to the 2015 state of the world (in >80% of 50,000 realisations) for more than twothirds of the 36 moderate targets, mostly related to environmental SDGs.

To illustrate, for the 2030 moderate targets, quality education (SDG 4), economic growth (SDG 8), and health and wellbeing (SDG 3) have a progress of 85%, 78%, and 59%, respectively ( Sustainable food (SDG 2) and clean energy (SDG 7) are the two goals with slower progress of 46% and 28% respectively ( Figure 2 ). In SDG 2, Fossil-Fuelled Development outperforms other pathways by 74% progress with on track or improving trends towards six out of seven moderate 2030 targets on food production and agricultural productivity (Figure 1a ). On the other hand, Fragmented World's progress is only 36%, being on track in achieving only two food-related targets by 2030. For SDG 7, the sustainable economic development in Green Recovery leads to progress of 47% towards targets, mostly due to achieving economic growth with a higher adoption of efficient end-use technologies and a faster transition to renewable energy (Extended Data Figure 4c -i). However, Fossil-Fuelled Development and Fragmented World have the slowest progress and are on track in only one targets for clean energy (respectively) due to heavy reliance on fossil energy (oil, gas, and then coal) production throughout the century (Supplementary   Figure 6e -v, f-v, g-v).

Inadequate progress by 2030 can be even worse with ≤0%, 5%, and 1% progress in biodiversity conservation (SDG 15), responsible production (SDG 11), and climate action (SDG 13), respectively. Projected progress in almost all 13 targets under these SDGs are either stagnating or deteriorating across the five modelled pathways by 2030. Poor environmental performance in all pathways except Green Recovery is largely the result of increasing demand for food production 31 , high meat consumption, and a growing energy-intensive economy which poses risks for environmental targets such as agricultural land expansion and intensive nitrogen fertiliser use (Extended Data Figure 4 ). The lowest achievements on these targets also translate into major consequences for ecosystem loss such as rapid decline in forest lands (in all pathways, 100% of realisations) and for destructive climate impacts such as faster global temperature increase (in all pathways, 99% of realisations), as raised in previous studies 21,32,33 (Figure 1a ). In each plot, the three bars indicate progress towards 2030, 2050, and 2100 targets. The bar indicates progress towards the moderate target and the error bar is the variation between progress towards ambitious (error bar bottom) and weak (error bar top) targets in across 50,000 simulated realisations of all future pathways combined. The annotated percentages are average progress across all pathways combined (grey text), the progress in the pathway with the worst performance (red text), and the progress in the pathway with the best performance (blue text), all percentages towards moderate targets by 2030, 2050, and 2100. The pie charts show the share of simulated realisations per each pathway (P1: Green Recovery, P2: Business As Usual, P3: Fragmented World, P4: Inequality, P5: Fossil-Fuelled Development). The pie chart colours show different progress levels (green: on track, yellow: improving, orange: stagnating, red: wrong direction) towards the moderate targets by 2100.

Overall, although individual target achievement varies between pathways and is sensitive to the uncertainty across different world realisations (Methods), the current UN agenda for sustainable development remains largely unmet by 2030, even in the most optimistic pathways (e.g., Green Recovery). This reflects tensions between socioeconomic and environmental goals 20,34 which lead to failure in concurrently achieving the 2030 targets.

Exploring pathways to reaching 2050 and 2100 targets. The short timeframe can have a complex effect on slow progress towards and tensions between the SDGs by 2030, and there is a higher chance of achieving more ambitious targets by 2050 and 2100. Looking at progress over the century (Figures 1 and 2 Figure 5b -i to b-iii; c-i to c-iii), but also with promising improvements to the major energy, climate, and ecological targets by 2050 and 2100. The Green Recovery pathway performs very well in the medium-term, with 42%, 54%, and 74% progress in biodiversity conservation, responsible production, and climate action by 2050, respectively ( Figure 2 ). This means being on track or improving for 9 out of 13 targets by 2050 (compared to only one improving target by 2030) even with a higher level of target ambition (Figure 1a ).

With a longer timeframe and even more ambitious targets, Green Recovery's progress in biodiversity conservation, responsible production, and climate action will become greater by 2100 (90%, 94%, and 84% respectively), being on track or improving on 12 out 13 targets (Figure 1a) . The cumulative effect of interventions (e.g., low carbon energy system, healthy diet with reduced meat consumption) incorporated in the Green Recovery pathway creates these promising long-term trajectories towards targets, which is central to turning the 'tide of change' 7 post-2030 to higher achievements. Priorities for transformative change in a new post-2030 agenda. Humanity is at a crossroads in planning for a post-pandemic world. Our projections of progress towards the SDGs showed that the 2030 agenda faces significant challenges limiting the chances of near-term success. Based on this evidence, we call for extending the current UN Agenda 2030's timeframe, with increasing levels of ambition in targets over the course of the century. This maintains the imperative for and global focus on sustainable development 5 over the long-term with a more radical approach 18,21 that disrupts the status quo, accelerates actions for achieving the SDGs, and puts a safety net in place where achieving ambitious long-term sustainability aspirations are not threatened by a failure to achieve some short-term goals. We showed (in Figures 1 and 2 ) that the Green Recovery pathway, over the medium-to long-term, can be a way forward for realising co-benefits between multiple goals 36 . As a step towards developing a more effective approach, we characterise the major transformative change needed across multiple sectors by analysing the distance to be bridged from current business-as-usual trajectories to the trajectories of a Green Recovery in a post-2030 timeframe (Figure 3 and Methods).

Compared to 2050 and 2100 business-as-usual, a Green Recovery primarily requires slowing population growth by 5% and 26%, along with a modest yet sustainable economic growth of 32% and 52%, and improving access to education by 10% and 40%, respectively. The demographic transition to a lower but more highly educated and prosperous population can lead to poverty reduction and gender equality. Higher educational levels also correlate with social norms and people's beliefs in the adoption of bolder actions such as improved family planning 37 , consuming less meat 15 and the appropriate attribution of extreme events to climate change 38,39 to lower population, avoid further deforestation, and reduce GHG emissions, respectively. Concurrently achieving these long-term targets and goals strongly relies on harnessing synergies and minimising trade-offs through steady progress across key parameters such as education level.

These socioeconomic changes, however, need to be further supported by transformations in the current consumption and production practices in energy, land, and food systems to mitigate some of the currently alarming trends of emissions and increasing temperature 16, 40 . Our energy systems need to be decarbonised more rapidly compared to business-as-usual trajectories with a decline of at least 36% and 80% in fossil energy (i.e., coal, oil, gas) production by 2050 and 2100, respectively. This also needs to be coupled with changing the patterns of energy consumption through a transition to 13% and 32% lower energy intensity services (compared to the business-as-usual) by mid and end of the century.

Cropland and pasture land need to be reduced by 7% and 10% compared to business-as-usual by 2050 and 2100 while continuing to increase food production. This requires improvement in crops and livestock yields and reducing food waste along with strong regulations on land-use change to limit deforestation and reverse the currently alarming trends of biodiversity loss 21 . These changes in the land sector should be facilitated by and intertwined with collaborative actions on food choices 15 through 39% and 50% reduction in landbased animal (i.e., meat and dairy) caloric intake in a healthy diet and a drop of 49% and 67% in livestock production by 2050 and 2100, respectively (compared to business-as-usual). This can also help those worst affected by the distributional impacts on food supply chains in a post-pandemic world.

While realising such transformative changes may come across as wishful thinking given current trends and the myriad of technical and political challenges that beset it, a pathway to Green Recovery is not totally out of reach. There are currently promising endeavours across several key sectors that could pave the way for transition to Green Recovery. Universal education is projected to be nearly achieved in many developed and developing countries, with supporting measures such as eliminating school fees and improving local access to schools to ensure equality 41 . In energy sector, there is already diverse global support for reducing energy intensity through digitalisation to transform energy efficiency and increase its value 42 . Reduction in energy demand in various countries is also complemented by policies such as carbon pricing for GHG emissions to accelerate the decarbonisation process 17, 40 . Coordinated efforts in food and land sectors have also emerged to promote healthy diet and sustainable agriculture through strategies such as investment in public health information and intensifying food production of high-quality outcomes 33,43 .

The global community needs to take additional steps to capitalise on these efforts in revising and extending the SDGs as an internationally agreed framework that works at the global, national, and local scale 44 and that can unite all sectors and countries behind a resilient economy and build coherent policies for a healthy planet. A Green Recovery pathway can create a touchpoint for science and policy discussions about resetting the global sustainability agenda of the 21 st century in the light of sustainable futures that is central for recovering from the pandemic with a better future for people and planet.

Leclère, D. et al. Bending the curve of terrestrial biodiversity needs an integrated strategy. Nature, doi:10.1038/s41586-020-2705-y (2020).

Randers 

FeliX is a system dynamics model that simulates complex interactions amongst ten sectors: population, education, economy, energy, water, land, food and diet change, carbon cycle, climate, and biodiversity. The Note that we aligned our pathways only with these five specific SSP-RCP combinations. We acknowledge that there were other potential combinations assessed in other studies 50 that we did not investigate here. For example in Green Recovery, we aligned the pathway with SSP1-RCP2.6 as the most common level of radiative forcing for SSP1 across 715 SSP-related studies 50 . However, Green Recovery could be also constructed inline with the pathways of more aggressive actions (e.g., EU, China, or the US pledges to comply with the Paris agreement) or more extreme mitigation (e.g., RCP1.9 or pathways proposed by the IPCC 1.5 51 ). This could make Green Recovery attain higher environmental achievements (e.g., faster reduction of fossil energy supply and emissions) compared to our study.

To construct the pathway narratives under the five SSP-RCP combinations, we elaborated on the qualitative assumptions of the original SSP storylines 25 and their sectoral extensions 26,52-55 . We also made assumptions describing the policy environment in both the near and long-term for climate mitigation to meet radiative forcing levels associated with each SSP. We made assumptions with respect to mitigating emissions from fossil fuels, bioenergy, and land via, for example, implementing carbon capture and storage for fossil fuels and bioenergy (BECCS) and imposing carbon price on fossil fuels. There was one set of policy assumptions associated with each pathway narrative, consistent with its inherent challenges for mitigation as outlined in 

To quantify the socioeconomic and environmental trends of each pathway narrative, we needed to identify those model parameters (i.e., pathway drivers) that are key in the projection of these trends. To identify pathway drivers from an initial list of 114 model parameters (as potential drivers) (Supplementary Table 2 60 , we adopted Morris elementary effects method and sensitivity index μ* 61,62 due to its ability to efficiently and effectively screen and identify benign parameters (i.e., factor fixing) from a large number of inputs in complex models 62, 63 . To compute μ*, we used the SALib library 64 implementation through the EMA workbench 65 Table 1 and Supplementary Table   4 ). The selected influential parameters were our pathway drivers which were annotated in Supplementary Subject to:

Where , , and denote socioeconomic drivers (related to population, economy, and education), the index of the driver, and the variation space of drivers for calibration, respectively. 

The SDG framework includes 17 goals and 231 unique indicators to measure progress towards 169 targets.

Here we explain how we operationalised the SDGs in FeliX via selecting and modelling a subset of indicators, setting science-based targets on the selected indicators, and measuring progress towards targets at the indicator and goal level (Extended Data Figure 3 ).

Commission (UNSC) 72 and other sources (e.g., OECD 73 , WHO 74 , FAO 75 , World Bank 76 ) based on three criteria. First, we looked at the global relevance of the potential output indicators generated by FeliX for measuring SDG progress (SDG applicability). Second, we assessed the ability of FeliX to quantify the SDG indicator (model fidelity). For those indicators that were not present in FeliX, we chose proxies. For example, we did not include an official indicator for biodiversity conservation such as the Red List Index as the required data is not produced in FeliX. Instead, we presented mean species abundance as a proxy indicator for biodiversity 21 . Third, we ensured that the selected indicators are amenable to the specification of quantitative performance thresholds for measuring progress towards the SDGs (target relevancy). We did not include the indicators that FeliX could project such as 'male or female population' which could not be meaningfully interpreted in terms of progress towards the SDGs. All indicators from the global SDG indicator framework 72 that passed these three criteria were implemented in the model (Extended Data Figure   3 )

Supplementary Equations 1 to 36.

The successful evaluation of progress towards the SDGs required a science-driven characterisation of targets 77 and a quantification of progress that can guide effective policy-making 32 . We defined nine different targets for each indicator using a mixed method approach to acknowledge the uncertainty around each target and the high sensitivity of SDG assessment to target specification. First, we set three target levels across the selected indicators: weak, moderate, and ambitious. At each level, we also set three time-bound targets to measure the progress by 2030, 2050, and 2100. We defined the ambitious target level across these target years following a decision tree 3,78 (Extended Data Figure 3 ).

First, we used available quantitative thresholds that were explicitly reflected in the official SDG framework (SDG absolute threshold) to set targets (3 indicators Third, wherever the SDG absolute threshold and technical optimum were not applicable, we followed the 2030 agenda's principle of "leave no one behind" and set the targets based on the average state of the top performing countries in a base year using historical documented data (5 indicators). Here, the global average as calculated by FeliX is expected to reach the levels of current top performing countries. In selecting the top performing countries, we removed the outliers from the list to reduce bias in our calculation. For example, a small country with limited agricultural arable land can have very low levels of fertilizer application. Therefore, the inclusion of this country as a top performer in calculating the target for the 'food and agriculture phosphorous balance' indicator can be misleading for larger countries with larger contribution to global food production. Where performance data was not available at the country level, we used regional data (e.g., OECD, continents).

Fourth, in the absence of any relevant targets, we nominally set a proportional improvement target in the indicator value from the world average in a base year guided by historical data (global improvement) (1 indicator). For example, 'total CO 2 emissions from agriculture' is an indicator with no absolute threshold mentioned in the original SDGs or technical optimum in other studies. The value of this indicator is also sensitive to the size of a country's agricultural sector. Therefore, leaving no one behind and the average of the top performers did not lead to a meaningful target. In this case, we used a level of global improvement as a target for the indicator. The base year for improvement can vary between indicators depending on the availability of data. The decision about the improvement rate from the base year value was made on a caseby-case basis for each indicator in a range between 5% improvement (e.g., in reducing CO 2 emissions from land-use) to 50% improvement (e.g., reducing coal production) from the global average as the 2030 ambitious target. The reduction or increase percentage was also informed by other model-based projections of SSPs to set an improvement rate ambitious enough to surpass the current trends while still being achievable.

For the moderate and weak target levels (across all three target years), we assumed that the moderate and weak indicate 50% and 25% progress towards the ambitious target from the base year value in 2015 with the exception of indicators for which moderate and weak targets were already available in the literature (e.g., radiative forcing from CO 2 emissions). Extended Data Table 2 Where ′ is the SDG and is the number of modelled indicators under goal . The index and its methodology were adopted from a similar index used in the global monitoring of the SDG progress 3 . We used the arithmetic mean with a normative assumption of equal weight across each goal's indicators to align with the global efforts to treat all indicators equally and only prioritise indicators when progress is lagging.

This also assumes that there is unlikely to be a consensus on SDG indicator priorities 78 . Based on the normalised values at the indicator level and aggregated indices at the goal level, we measured world progress towards targets at four levels. On track indicates that progress highly likely to achieve (or exceed) global sustainability targets (i.e., indicator and goal level target achievement ≥100%). Improving indicates positive trends towards the goal and indicator level targets but meeting them is unlikely, so challenges remain (i.e., target achievement between 50 and 100%). Stagnating indicates performance following current trends, little chance of target achievement, and significant challenges remain (i.e., target achievement between 0 and 50%). Wrong direction indicates a deteriorating trend (i.e., target achievement between ≤0%).

We evaluated the five pathways in terms of the modelled indicators and progress towards the SDG targets through exploratory ensemble modelling 28, 86 we identified the most promising pathway (i.e., Green Recovery) in the 21 st century. We then characterised this identified pathway across multiple sectors (e.g., population, education, decarbonisation, food) and

quantified the steps to be taken from the business-as-usual trajectories to realise the identified pathway ( Figure 3 ).

Results are available at https://github.com/enayatmoallemi/ Moallemi_et_al_SDG_SSP_Assessment. Extended Data Table 1 . Descriptions of modelled pathway drivers in FeliX. In the first column, pathway drivers (e.g., population growth) are categorised into socioeconomic, energy and climate, land, and food and diet change in relation to their impacts on different SDGs. Each pathway driver is associated with a number of model parameters in FeliX. The fraction value in front each pathway driver in the first column shows the number of influential model parameters (that were identified through sensitivity analysis) to the total number of parameters modelled in FeliX. For example, we modelled 'economic growth' through five uncertain parameters two of which were identified as influential to be included in the quantification of pathways. From the second to the sixth column, the triangles qualitatively represent the direction and magnitude of change in the calibrated pathway drivers. The signs  represents a strong increase,  increase,  no change from business-as-usual,  is decrease, and  is strong decrease. The last column shows the effect of each driver on the related SDGs. 'P' and 'D' indicate that the increasing driver has pressurising (i.e., creating barriers) and depressurising (i.e., facilitating) effects on related SDGs respectively. See Supplementary  Table 4 

Identify pathway drivers •Develop 5 qualitative assumptions for socioeconomic and environmental drivers aligned with five SSP-RCP combinations.

•Identify 60 important model parameters (i.e., pathway drivers) in FeliX for the narratives through global sensitivity analysis.

•Calibrate FeliX's socioeconomic, energy and climate, land-use, and food and diet scenario drivers under the assumptions of five pathway (SSP-RCP) narratives.

•Validate the simulated pathway projections with the SSP-RCP projections of other IAMs across 20 control variables.

•Model 36 SDG indicators across 8 SDGs in FeliX within the model scope.

•Identify 9 target values (3 target levels x 3 target years) for each indicator based on original SDG framework, science-based metrics, the 'leave no one behind' principle.

•Normalise the indicators' projections and targets between 0% and 100% and computing the distance taken from 2015 and the gap to achieve the targets.

•Aggregate the normalised values of indicators into a SDG index and measuring the progress at the goal level between 0% and 100%.

Explore pathway x SDG interactions under uncertainty

•Evaluate 50,000 realisations of pathways with respect to the targets for each indicator and aggregated in each SDG.

•Assessing comparative performance of pathways in meeting the targets under uncertainty.

Elaborate the change need to achieve the post-2030 SDGs 

Extended Data Figure 5 . Performance of global pathways towards SDG targets in 2100 under five SSP-compliant pathways.

Results for the performance of each pathway are represented by a specifically colour coded violin plot and boxplot. The violin shows the distribution of pathway's performance across 10,000 simulated realisations of each pathway. The box shows the interquartile range (centre line is median) of these simulated realisations while the whiskers extend to show the rest of the distribution, except for points that are identified as outliers. The coloured lines mark weak, moderate, and ambitious targets in 2100 (Extended Data Table 2 ). The red and blue (discrete) colour gradients specify the percentage that the pathway's performance is deteriorating or improving from the state of the world in 2015. They also show the progress direction and can be used to understand how ambitious the target levels are in comparison the 2015 state of the world. Energy consumption per unit of GWP production, as an indication of how much energy is used to produce one unit of economic output. Lower ratio indicates that less energy is used to produce one unit of output. 

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• Supplementary Table 1