Achievements and needs for the climate change scenario framework

Strategies for integrating scientific evidence in water policy and law in the face of uncertainty

Understanding how human actions and environmental change affect water resources is crucial for addressing complex water management issues. The scientific tools that can produce the necessary information are ecological indicators, referring to measurable properties of the ecosystem state; environmental monitoring, the data collection process that is required to evaluate the progress towards reaching water management goals; mathematical models, linking human disturbances with the ecosystem state to predict environmental impacts; and scenarios, assisting in long-term management and policy implementation. Paradoxically, despite the rapid generation of data, evolving scientific understanding, and recent advancements in systems modeling, there is a striking imbalance between knowledge production and knowledge utilization in decision-making. In this paper, we examine the role and potential capacity of scientific tools in guiding governmental decision-making processes and identify the most critical disparities between water management, policy, law, and science. We demonstrate how the complex, uncertain, and gradually evolving nature of scientific knowledge might not always fit aptly to the legislative and policy processes and structures. We contend that the solution towards increased understanding of socio-ecological systems and reduced uncertainty lies in strengthening the connections between water management theory and practice, among the scientific tools themselves, among different stakeholders, and among the social, economic, and ecological facets of water quality management, law, and policy. We conclude by tying in three knowledge-exchange strategies, namely - adaptive management, Driver-Pressure-Status-Impact-Response (DPSIR) framework, and participatory modeling - that offer complementary perspectives to bridge the gap between science and policy.

Advancing SSP-aligned scenarios of shipping toward 2050

Developing comprehensive scenarios for the shipping sector has been a challenge for the Integrated Assessment Model (IAMs) community, influencing how attainable decarbonization is in the sector, and for Earth System Models (ESMs), impacting the climate contribution of shipping emissions. Here we present an approach to develop spatially explicit energy demand projections for shipping in alignment with the Shared Socioeconomic Pathways framework and IAMs projections of global fossil fuel demand. Our results show that shipping could require between 14 and 20 EJ by 2050, corresponding to a 3% and 44% increase from 2018 for the SSP1-1.9 and SSP3-7.0 scenarios. Furthermore, the energy projections we present in this publication can be combined with different fuel mixes to derive emission inventories for climate modeling and, thus, improve our understanding of the various challenges in mitigating emissions for shipping. Through that, we aim to present a framework to incorporate detailed spatial shipping inventories and increase transparency for the scientific community.

Substantially reducing global PM2.5-related deaths under SDG3.9 requires better air pollution control and healthcare

The United Nations' Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP.

Past dynamics and future prediction of the impacts of land use cover change and climate change on landscape ecological risk across the Mongolian plateau

Land use/land cover (LULC) change and climate change are interconnected factors that affect the ecological environment. However, there is a lack of quantification of the impacts of LULC change and climate change on landscape ecological risk under different shared socioeconomic pathways and representative concentration pathways (SSP-RCP) on the Mongolian Plateau (MP). To fill this knowledge gap and understand the current and future challenges facing the MP's land ecological system, we conducted an evaluation and prediction of the effects of LULC change and climate change on landscape ecological risk using the landscape loss index model and random forest method, considering eight SSP-RCP coupling scenarios. Firstly, we selected MCD12Q1 as the optimal LULC product for studying landscape changes on the MP, comparing it with four other LULC products. We analyzed the diverging patterns of LULC change over the past two decades and observed significant differences between Mongolia and Inner Mongolia. The latter experienced more intense and extensive LULC change during this period, despite similar climate changes. Secondly, we assessed changes in landscape ecological risk and identified the main drivers of these changes over the past two decades using a landscape index model and random forest method. The highest-risk zone has gradually expanded, with a 30% increase compared to 2001. Lastly, we investigated different characteristics of LULC change under different scenarios by examining future LULC products simulated by the FLUS model. We also simulated the dynamics of landscape ecological risks under these scenarios and proposed an adaptive development strategy to promote sustainable development in the MP. In terms of the impact of climate change on landscape ecological risk, we found that under the same SSP scenario, increasing RCP emission concentrations significantly increased the areas with high landscape ecological risk while decreasing areas with low risk. By integrating quantitative assessments and scenario-based modeling, our study provides valuable insights for informing sustainable land management and policy decisions in the region.

Characterization and transformation of the CabHLH18 gene from hot pepper to enhance waterlogging tolerance

Basic helix-loop-helix (bHLH) proteins are important in abiotic stress control. Here, a specific bHLH transcription factor gene, CabHLH18, from a strong waterlogging-tolerant pepper cultivar, 'ZHC2', was successfully cloned. The CabHLH18 gene presented a coding sequence length of 1,056 bp, encoding 352 amino acids, and the protein was the closest to Capsicum annuum XM016694561.2 protein. The CabHLH18 protein was located in the nucleus. The transformation of the CabHLH18 overexpression vector into the plumules of hot peppers, 'DFZJ' and 'ZHC1', exhibited 21.37% and 22.20% efficiency, respectively. The root length, plant height, and fresh weight of the 'DFZJ' overexpression lines were greater than those of wild-type (WT) plants under waterlogging conditions. Compared with the WT plants, the overexpression lines generally showed greater contents of water, the amino acid, proline, soluble sugar, root viability, and superoxide dismutase activity, but lower malondialdehyde content under waterlogging conditions. Plant fresh weight, amino acids, proline, and soluble sugar levels of the overexpression lines were 39.17%, 45.03%, 60.67%, and 120.18% greater, respectively, compared with the WT plants at 24 h after waterlogging stress. Therefore, the CabHLH18 gene could be implicated in conferring waterlogging tolerance in hot peppers and holds promise for enhancing their overall waterlogging tolerance.

Stakeholder-driven transformative adaptation is needed for climate-smart nutrition security in sub-Saharan Africa

Improving nutrition security in sub-Saharan Africa under increasing climate risks and population growth requires a strong and contextualized evidence base. Yet, to date, few studies have assessed climate-smart agriculture and nutrition security simultaneously. Here we use an integrated assessment framework (iFEED) to explore stakeholder-driven scenarios of food system transformation towards climate-smart nutrition security in Malawi, South Africa, Tanzania and Zambia. iFEED translates climate-food-emissions modelling into policy-relevant information using model output implication statements. Results show that diversifying agricultural production towards more micronutrient-rich foods is necessary to achieve an adequate population-level nutrient supply by mid-century. Agricultural areas must expand unless unprecedented rapid yield improvements are achieved. While these transformations are challenging to accomplish and often associated with increased greenhouse gas emissions, the alternative for a nutrition-secure future is to rely increasingly on imports, which would outsource emissions and be economically and politically challenging given the large import increases required.

Spread in climate policy scenarios unravelled

Analysis of climate policy scenarios has become an important tool for identifying mitigation strategies, as shown in the latest Intergovernmental Panel on Climate Change Working Group III report1. The key outcomes of these scenarios differ substantially not only because of model and climate target differences but also because of different assumptions on behavioural, technological and socio-economic developments2-4. A comprehensive attribution of the spread in climate policy scenarios helps policymakers, stakeholders and scientists to cope with large uncertainties in this field. Here we attribute this spread to the underlying drivers using Sobol decomposition5, yielding the importance of each driver for scenario outcomes. As expected, the climate target explains most of the spread in greenhouse gas emissions, total and sectoral fossil fuel use, total renewable energy and total carbon capture and storage in electricity generation. Unexpectedly, model differences drive variation of most other scenario outcomes, for example, in individual renewable and carbon capture and storage technologies, and energy in demand sectors, reflecting intrinsic uncertainties about long-term developments and the range of possible mitigation strategies. Only a few scenario outcomes, such as hydrogen use, are driven by other scenario assumptions, reflecting the need for more scenario differentiation. This attribution analysis distinguishes areas of consensus as well as strong model dependency, providing a crucial step in correctly interpreting scenario results for robust decision-making.

Contribution of land use and cover change (LUCC) to the global terrestrial carbon uptake

Terrestrial carbon uptake is critical to the removal of greenhouse gases and mitigation of global warming, which are closely related to land use and cover change (LUCC). However, understanding terrestrial carbon uptake and the LUCC contribution remains unclear because of complex interactions with other drivers (particularly climate change). By proposing an innovative approach of "trajectory analysis", this study aimed to isolate the LUCC contribution to terrestrial carbon uptake over different scales. Methodologically, global land was first divided into sub-regions of land transformations and stable land trajectories. Then, the carbon uptake change in the stable land trajectory was taken as a synthetic influence of climate change, which was used as a reference to isolate the carbon uptake alternation generated from the LUCC contribution in the land transformation trajectories. Finally, future LUCC and the terrestrial carbon uptake response were predicted under different development pathways. The results showed the global mean net ecosystem production (NEP) was 27.44 ± 36.51 g C m-2 yr-1 in the past two decades (2001-2019), generating 3.15 ± 0.88 Pg C yr-1 of the total terrestrial carbon uptake. Both the NEP and total carbon uptake showed significant increasing trends. Specifically, the mean NEP increased from 17.96 g C m-2 yr-1 in 2001 to 37.37 g C m-2 yr-1 in 2019, with the trend written as y = 1.20× + 15.20 (R2 = 0.62, p < 0.01). Meanwhile, the total carbon uptake increased from 2.35 Pg C yr-1 in 2001 to 4.13 Pg C yr-1 in 2019, which could be written as y = 0.12× + 1.93 (R2 = 0.56, p < 0.01). Climate change acted as the dominant factor for the trends at the global scale, which contributed 21.26 g C m-2 yr-1 and 1.59 Pg C yr-1 of the mean NEP and total carbon uptake changes in the stable land trajectories (94.30 million km2 that covered 63.29 % of the global land area), and the historical LUCC contributed -6.30 g C m-2 yr-1 (-40.85 %) and - 0.046 Pg C yr-1 (-57.50 %) of the mean NEP and the total carbon uptake change in the land transformation trajectories (6.64 million km2 that covered 4.46 % of the global land area), respectively. The maximum LUCC contribution (-61.85 g C m-2 yr-1) to the mean NEP occurred in the land transformations from evergreen needleleaf forests to woody savannas, while the maximum contribution (-0.034 Pg C y-1) to total carbon uptake was in the deforested regions from evergreen broadleaf forests to woody savannas. Eight SSP-RCP scenarios predictions demonstrated that future terrestrial carbon uptake would increase by an average of 0.015 Pg C yr-1 in 2100 due to global afforestation. SSP4-3.4 and SSP5-3.4 had the greatest potential for increasing carbon uptake, which is expected to reach a maximum increase (0.045 Pg C yr-1) in 2100. In contrast, the minimum terrestrial carbon uptake would occur in SSP5-8.5, which had the highest CO2 emissions. In conclusion, although relatively limited at the global scale, LUCC (particularly forest change) exerted an unneglectable role on terrestrial carbon uptake in land transformation regions. The results of this study will help to clarify terrestrial carbon uptake dynamics and provide a basis for carbon neutral and climatic adaptation.

The social costs of tropical cyclones

Tropical cyclones (TCs) can adversely affect economic development for more than a decade. Yet, these long-term effects are not accounted for in current estimates of the social cost of carbon (SCC), a key metric informing climate policy on the societal costs of greenhouse gas emissions. We here derive temperature-dependent damage functions for 41 TC-affected countries to quantify the country-level SCC induced by the persistent growth effects of damaging TCs. We find that accounting for TC impacts substantially increases the global SCC by more than 20%; median global SCC increases from US$ 173 to US$ 212 per tonne of CO2 under a middle-of-the-road future emission and socioeconomic development scenario. This increase is mainly driven by the strongly TC-affected major greenhouse gas emitting countries India, USA, China, Taiwan, and Japan. This suggests that the benefits of climate policies could currently be substantially underestimated. Adequately accounting for the damages of extreme weather events in policy evaluation may therefore help to prevent a critical lack of climate action.

Projected Change in the Burden of Excess Cardiovascular Deaths Associated With Extreme Heat by Midcentury (2036-2065) in the Contiguous United States

BACKGROUND

Climate change is causing an increase in extreme heat. Individuals with cardiovascular disease are at high risk of heat-related adverse health effects. How the burden of extreme heat-associated cardiovascular deaths in the United States will change with the projected rise in extreme heat is unknown.

METHODS

We obtained data on cardiovascular deaths among adults and the number of extreme heat days (maximum heat index ≥90 °F [32.2 °C]) in each county in the contiguous United States from 2008 to 2019. Based on representative concentration pathway trajectories that model greenhouse gas emissions and shared socioeconomic pathways (SSP) that model future socioeconomic scenarios and demographic projections, we obtained county-level projected numbers of extreme heat days and populations under 2 scenarios for the midcentury period 2036 to 2065: SSP2-4.5 (representing demographic projections from a "middle-of-the-road" socioeconomic scenario and an intermediate increase in emissions) and SSP5-8.5 (demographic projections in an economy based on "fossil-fueled development" and a large increase in emissions). The association of cardiovascular mortality with extreme heat was estimated with a Poisson fixed-effects model. Using estimates from this model, the projected number of excess cardiovascular deaths associated with extreme heat was calculated.

RESULTS

Extreme heat was associated with 1651 (95% CI, 921-2381) excess cardiovascular deaths per year from 2008 to 2019. By midcentury, extreme heat is projected to be associated with 4320 (95% CI, 2369-6272) excess deaths annually, which is an increase of 162% (95% CI, 142-182) under SSP2-4.5, and 5491 (95% CI, 3011-7972) annual excess deaths, which is an increase of 233% (95% CI, 206-259) under SSP5-8.5. Elderly adults are projected to have a 3.5 (95% CI, 3.2-3.8) times greater increase in deaths in the SSP2-4.5 scenario compared with nonelderly adults. Non-Hispanic Black adults are projected to have a 4.6 (95% CI, 2.8-6.4) times greater increase compared with non-Hispanic White adults. The projected change in deaths was not statistically significantly different for other race and ethnicity groups or between men and women.

CONCLUSIONS

By midcentury, extreme heat is projected to be associated with a significantly greater burden of excess cardiovascular deaths in the contiguous United States.

Aerosols overtake greenhouse gases causing a warmer climate and more weather extremes toward carbon neutrality

To mitigate climate warming, many countries have committed to achieve carbon neutrality in the mid-21st century. Here, we assess the global impacts of changing greenhouse gases (GHGs), aerosols, and tropospheric ozone (O3) following a carbon neutrality pathway on climate and extreme weather events individually using the Community Earth System Model version 1 (CESM1). The results suggest that the future aerosol reductions significantly contribute to climate warming and increase the frequency and intensity of extreme weathers toward carbon neutrality and aerosol impacts far outweigh those of GHGs and tropospheric O3. It reverses the knowledge that the changing GHGs dominate the future climate changes as predicted in the middle of the road pathway. Therefore, substantial reductions in GHGs and tropospheric O3 are necessary to reach the 1.5 °C warming target and mitigate the harmful effects of concomitant aerosol reductions on climate and extreme weather events under carbon neutrality in the future.

Rethinking personal carbon trading (PCT) mechanism: A comprehensive review

The implementation of Personal Carbon Trading (PCT) holds promise in facilitating a noteworthy contribution towards the attainment of emissions reduction predicated on consumption patterns and consequently motivating lifestyle modifications. As individual consumption behaviors usually lead to continuous changes in carbon emissions, it is crucial to rethink PCT from a systematic perspective. This review employed a bibliometric analysis of 1423 papers related to PCT, highlighting the key themes of carbon emissions from energy consumption, climate change, and public opinion on policies in the context of PCT. Most of the existing PCT researches focus on theoretical assumptions and public attitudes, while the quantification of carbon emissions and simulation of PCT require further investigation. Furthermore, the concept of Tan Pu Hui is seldom addressed in PCT studies and case analyses. Moreover, there are limited PCT schemes worldwide that can be directly implemented in practice, leading to a scarcity of large-scale, high-participation case studies. To address these gaps, this review proposes a framework to clarify how PCT can stimulate individual emission reductions on the consumption side, comprising two phases, from motivation to behavior and behavior to target. Future endeavors should prioritize the enhancement of the systematic study of the theoretical foundation of PCT, encompassing carbon emissions accounting and policy design, the incorporation of cutting-edge technology, and the reinforcement of integrated policy practice. This review serves as a valuable reference for future research endeavors and policymaking efforts.

Towards diverse agricultural land uses: socio-ecological implications of European agricultural pathways for a Swiss orchard region

Diverse agricultural land uses are a typical feature of multifunctional landscapes. The uncertain change in the drivers of global land use, such as climate, market and policy technology and demography, challenges the long-term management of agricultural diversification. As these global drivers also affect smaller scales, it is important to capture the traits of regionally specific farm activities to facilitate adaptation to change. By downscaling European shared socioeconomic pathways (SSPs) for agricultural and food systems, combined with representative concentration pathways (RCP) to regionally specific, alternative socioeconomic and climate scenarios, the present study explores the major impacts of the drivers of global land use on regional agriculture by simulating farm-level decisions and identifies the socio-ecological implications for promoting diverse agricultural landscapes in 2050. A hilly orchard region in northern Switzerland was chosen as a case study to represent the multifunctional nature of Swiss agriculture. Results show that the different regionalised pathways lead to contrasting impacts on orchard meadows, production levels and biodiversity. Increased financial support for ecological measures, adequate farm labour supplies for more labour-intensive farming and consumer preferences that favour local farm produce can offset the negative impacts of climate change and commodity prices and contribute to agricultural diversification and farmland biodiversity. However, these conditions also caused a significant decline in farm production levels. This study suggests that considering a broader set of land use drivers beyond direct payments, while acknowledging potential trade-offs and diverse impacts across different farm types, is required to effectively manage and sustain diversified agricultural landscapes in the long run.

Supplementary information

The online version contains supplementary material available at 10.1007/s10113-023-02092-5.

Range Dynamics of Striped Field Mouse (Apodemus agrarius) in Northern Eurasia under Global Climate Change Based on Ensemble Species Distribution Models

The striped field mouse (Apodemus agrarius Pallas, 1771) is a widespread species in Northern Eurasia. It damages crops and carries zoonotic pathogens. Its current and future range expansion under climate change may negatively affect public health and the economy, warranting further research to understand the ecological and invasive characteristics of the species. In our study, we used seven algorithms (GLM, GAM, GBS, FDA, RF, ANN, and MaxEnt) to develop robust ensemble species distribution models (eSDMs) under current (1970-2000) and future climate conditions derived from global circulation models (GCMs) for 2021-2040, 2041-2060, 2061-2080, and 2081-2100. Simulation of climate change included high-, medium-, and low-sensitivity GCMs under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We analyzed the habitat suitability across GCMs and scenarios by constructing geographical ranges and calculating their centroids. The results showed that the range changes depended on both the sensitivity of GCMs and scenario. The main trends were range expansion to the northeast and partial loss of habitat in the steppe area. The striped field mouse may form a continuous range from Central Europe to East Asia, closing the range gap that has existed for 12 thousand years. We present 49 eSDMs for the current and future distribution of A. agrarius (for 2000-2100) with quantitative metrics (gain, loss, change) of the range dynamics under global climate change. The most important predictor variables determining eSDMs are mean annual temperature, mean diurnal range of temperatures, the highest temperature of the warmest month, annual precipitation, and precipitation in the coldest month. These findings could help limit the population of the striped field mouse and predict distribution of the species under global climate change.

Predicting current and future high-risk areas for vectors and reservoirs of cutaneous leishmaniasis in Iran

Climate change will affect the distribution of species in the future. To determine the vulnerable areas relating to CL in Iran, we applied two models, MaxEnt and RF, for the projection of the future distribution of the main vectors and reservoirs of CL. The results of the models were compared in terms of performance, species distribution maps, and the gain, loss, and stable areas. The models provided a reasonable estimate of species distribution. The results showed that the Northern and Southern counties of Iran, which currently do not have a high incidence of CL may witness new foci in the future. The Western, and Southwestern regions of the Country, which currently have high habitat suitability for the presence of some vectors and reservoirs, will probably significantly decrease in the future. Furthermore, the most stable areas are for T. indica and M. hurrianae in the future. So that, this species may remain a major reservoir in areas that are present under current conditions. With more local studies in the field of identifying vulnerable areas to CL, it can be suggested that the national CL control guidelines should be revised to include a section as a climate change adaptation plan.

Assembling the climate story: use of storyline approaches in climate-related science

Storylines are introduced in climate science to provide unity of discourse, integrate the physical and socioeconomic components of phenomena, and make climate evolution more tangible. The use of this concept by multiple scholar communities and the novelty of some of its applications renders the concept ambiguous nonetheless, because the term hides behind a wide range of purposes, understandings, and methodologies. This semi-systematic literature review identifies three approaches that use storylines as a keystone concept: scenarios-familiar for their use in IPCC reports-discourse-analytical approaches, and physical climate storylines. After screening peer-reviewed articles that mention climate and storylines, 270 articles are selected, with 158, 55, and 57 in each category. The results indicate that each scholarly community works with a finite and different set of methods and diverging understandings. Moreover, these approaches have received criticism in their assembly of storylines: either for lacking explicitness or for the homogeneity of expertise involved. This article proposes that cross-pollination among the approaches can improve the usefulness and usability of climate-related storylines. Among good practices are the involvement of a broader range of scientific disciplines and expertise, use of mixed-methods, assessment of storylines against a wider set of quality criteria, and targeted stakeholder participation in key stages of the process.

Landscape Change Scenarios: Developing Participatory Tools for Enhancing Resilience to Climate Change

The impacts of climate change on people and ecosystems have been studied at both local and global levels. The environment is expected to change significantly, and the role of local communities in shaping more resilient landscapes is considered crucial. This research focuses on rural regions highly susceptible to climate change impacts. The objective was to enhance conditions for climate resilient development on a microlocal level by encouraging diverse stakeholders to participate in developing sustainable landscape management. This paper introduces a novel interdisciplinary mixed-method approach to landscape scenario development, combining research-driven and participatory approaches and integrating quantitative methods with qualitative ethnographic inquiry. Two scenarios for 2050 were built: a research-driven, business-as-usual scenario accounting for mandatory adaptation policies and an optimistic scenario combining research-driven and participatory approaches, including additional feasible community-based measures. While the differences between the projected land use seem to be relatively subtle, the optimistic scenario would in fact lead to a considerably more resilient landscape. The results highlight the role of interdisciplinarity and ethnography in gaining good local knowledge and building an atmosphere of trust. These factors supported the research credibility, strengthened the legitimacy of the intervention in local affairs, and contributed to the active participation of the stakeholders. We argue that despite its time, intense effort and limited direct policy impact, the mixed-method approach is highly suitable for the microlocal level. It encourages citizens to think about how their environment is threatened by climate change impacts and increases their willingness to contribute to climate resilience.

Exploring spatial feedbacks between adaptation policies and internal migration patterns due to sea-level rise

Climate change-induced sea-level rise will lead to an increase in internal migration, whose intensity and spatial patterns will depend on the amount of sea-level rise; future socioeconomic development; and adaptation strategies pursued to reduce exposure and vulnerability to sea-level rise. To explore spatial feedbacks between these drivers, we combine sea-level rise projections, socioeconomic projections, and assumptions on adaptation policies in a spatially-explicit model ('CONCLUDE'). Using the Mediterranean region as a case study, we find up to 20 million sea-level rise-related internal migrants by 2100 if no adaptation policies are implemented, with approximately three times higher migration in southern and eastern Mediterranean countries compared to northern Mediterranean countries. We show that adaptation policies can reduce the number of internal migrants by a factor of 1.4 to 9, depending on the type of strategies pursued; the implementation of hard protection measures may even lead to migration towards protected coastlines. Overall, spatial migration patterns are robust across all scenarios, with out-migration from a narrow coastal strip and in-migration widely spread across urban settings. However, the type of migration (e.g. proactive/reactive, managed/autonomous) depends on future socioeconomic developments that drive adaptive capacity, calling for decision-making that goes well beyond coastal issues.

Research needs for a food system transition

The global food system, and animal agriculture in particular, is a major and growing contributor to climate change, land system change, biodiversity loss, water consumption and contamination, and environmental pollution. The copious production and consumption of animal products are also contributing to increasingly negative public health outcomes, particularly in wealthy and rapidly industrializing countries, and result in the slaughter of trillions of animals each year. These impacts are motivating calls for reduced reliance on animal-based products and increased use of replacement plant-based products. However, our understanding of how the production and consumption of animal products, as well as plant-based alternatives, interact with important dimensions of human and environment systems is incomplete across space and time. This inhibits comprehensively envisioning global and regional food system transitions and planning to manage the costs and synergies thereof. We therefore propose a cross-disciplinary research agenda on future target-based scenarios for food system transformation that has at its core three main activities: (1) data collection and analysis at the intersection of animal agriculture, the environment, and societal well-being, (2) the construction of target-based scenarios for animal products informed by these new data and empirical understandings, and (3) the evaluation of impacts, unintended consequences, co-benefits, and trade-offs of these target-based scenarios to help inform decision-making.

Closing the Gap between Carbon Neutrality Targets and Action: Technology Solutions for China's Key Energy-Intensive Sectors

Facing significant carbon emissions annually, China requires a clear decarbonization strategy to meet its climate targets. This study presents a MESSAGEix-CAEP model to explore Chinese decarbonization pathways and their cost-benefit under two mitigation scenarios by establishing connections between five energy-intensive sectors based on energy and material flows. The results indicated the following: 1) Interaction and feedback between sectors should not be disregarded. The electrification process of the other four sectors was projected to increase electricity production by 206%, resulting in a higher power demand than current forecasts. 2) The marginal abatement cost to achieve carbon neutrality across all five sectors was 2189 CNY/tCO₂, notably higher than current Chinese carbon emission trading prices. 3) The cost-benefit analysis indicates that a more ambitious abatement strategy would decrease the marginal abatement cost and result in a higher net carbon abatement benefit. The cumulative net benefit of carbon reduction was 7.8 trillion CNY under ambitious mitigation scenario, 1.3 trillion CNY higher than that under current Chinese mitigation scenario. These findings suggest that policy-makers should focus on the interaction effects of decarbonization pathways between sectors and strengthen their decarbonization efforts to motivate early carbon reduction.

The contribution of demographic changes to future heat-related health burdens under climate change scenarios

Anthropogenic climate change will have a detrimental impact on global health, including the direct impact of higher ambient temperatures. Existing projections of heat-related health outcomes in a changing climate often consider increasing ambient temperatures alone. Population growth and structure has been identified as a key source of uncertainty in future projections. Age acts as a modifier of heat risk, with heat-risk generally increasing in older age-groups. In many countries the population is ageing as lower birth rates and increasing life expectancy alter the population structure. Preparing for an older population, in particular in the context of a warmer climate should therefore be a priority in public health research and policy. We assess the level of inclusion of population growth and demographic changes in research projecting exposure to heat and heat-related health outcomes. To assess the level of inclusion of population changes in the literature, keyword searches of two databases were implemented, followed by reference and citation scans to identify any missed papers. Relevant papers, those including a projection of the heat health burden under climate change, were then checked for inclusion of population scenarios. Where sensitivity to population change was studied the impact of this on projections was extracted. Our analysis suggests that projecting the heat health burden is a growing area of research, however, some areas remain understudied including Africa and the Middle East and morbidity is rarely explored with most studies focusing on mortality. Of the studies pairing projections of population and climate, specifically SSPs and RCPs, many used pairing considered to be unfeasible. We find that not including any projected changes in population or demographics leads to underestimation of health burdens of on average 64 %. Inclusion of population changes increased the heat health burden across all but two studies.

Integrated climate, ecological and socioeconomic scenarios for the whale watching sector

Unprecedented human induced changes to the climate system have already contributed to a variety of observed impacts to both ecosystems and populations. Decision-makers demand impact assessments at the regional-to-local scale to be able to plan and define effective climate action measures. Integrated socio-ecological assessments that properly consider system uncertainties require the use of prospective scenarios that project potential climate impacts, while accounting for sectoral exposure and adaptive capacity. Here we provide an integrated assessment of climate change to the whale watching sector by: 1) extending the European Shared Socio-economic Pathways (Eur-SSPs) and developing four whale watching SSP narratives (WW-SSPs) and 2) characterize each key element comprised in the WW-SSPs for the time period 2025-2055. We applied this approach in a case study for the Macaronesia region where we developed scenarios which integrate the socio-economic (WW-SSPs), climate (RCPs) and ecological (species' thermal suitability responses) dimensions of whale watching. These scenarios were used by local stakeholders to identify the level of preparedness of the whale watching sector. When confronted with scenarios that combine this ecological dimension with projected climate changes and the four different socioeconomic narratives, stakeholders assessed the whale watching sector in Macaronesia as being somewhat prepared for a Sustainable World and a Fossil Fuel Development World, but somewhat unprepared for a Rivalry World. No consensus was reached regarding the sector's preparedness level under an Inequality World scenario. Our study demonstrates the importance of considering multiple dimensions when assessing the potential challenges posed by climate change and provides a needed resource to help the whale watching sector in Macaronesia, and elsewhere, in its effort to devise efficient climate action policies and strategies.

Climate change multi-model projections in CMIP6 scenarios in Central Hokkaido, Japan

Simulation of future climate changes, especially temperature and rainfall, is critical for water resource management, disaster mitigation, and agricultural development. Based on the category-wise indicator method, two preferred Global Climate Models (GCMs) for the Ishikari River basin (IRB), the socio-economic center of Hokkaido, Japan, were examined from the newly released Coupled Model Intercomparison Project Phase 6 (CMIP6). Climatic variables (maximum/minimum temperature and precipitation) were projected by the Statistical DownScaling Model (SDSM) under all shared socioeconomic pathway-representative concentration pathway (SSP-RCP) scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, SSP5-3.4OS, and SSP5-8.5) in two phases: 2040-2069 (2040s) and 2070-2099 (2070s), with the period of 1985-2014 as the baseline. Predictors of SDSM were derived from CMIP6 GCMs and the reanalysis dataset NOAA-CIRES-DOE 20th Century Reanalysis V3 (20CRv3). Results showed that CMIP6 GCMs had a significant correlation with temperature measurements, but could not represent precipitation features in the IRB. The constructed SDSM could capture the characteristics of temperature and precipitation during the calibration (1985-1999) and validation (2000-2014) phases, respectively. The selected GCMs (MIROC6 and MRI-ESM-2.0) generated higher temperature and less rainfall in the forthcoming phases. The SSP-RCP scenarios had an apparent influence on temperature and precipitation. High-emission scenarios (i.e., SSP5-8.5) would project a higher temperature and lower rainfall than the low-emission scenarios (e.g., SSP1-1.9). Spatial-temporal analysis indicated that the northern part of the IRB is more likely to become warmer with heavier precipitation than the southern part in the future. Higher temperature and lower rainfall were projected throughout the late twenty-first century (2070s) than the mid-century (2040s) in the IRB. The findings of this study could be further used to predict the hydrological cycle and assess the ecosystem's sustainability.

Better insurance could effectively mitigate the increase in economic growth losses from U.S. hurricanes under global warming

Global warming is likely to increase the proportion of intense hurricanes in the North Atlantic. Here, we analyze how this may affect economic growth. To this end, we introduce an event-based macroeconomic growth model that temporally resolves how growth depends on the heterogeneity of hurricane shocks. For the United States, we find that economic growth losses scale superlinearly with shock heterogeneity. We explain this by a disproportional increase of indirect losses with the magnitude of direct damage, which can lead to an incomplete recovery of the economy between consecutive intense landfall events. On the basis of two different methods to estimate the future frequency increase of intense hurricanes, we project annual growth losses to increase between 10 and 146% in a 2°C world compared to the period 1980-2014. Our modeling suggests that higher insurance coverage can compensate for this climate change-induced increase in growth losses.

Drought patterns: their spatiotemporal variability and impacts on maize production in Limpopo province, South Africa

Due to global climate change, droughts are likely to become more frequent and more severe in many regions such as in South Africa. In Limpopo, observed high climate variability and projected future climate change will likely increase future maize production risks. This paper evaluates drought patterns in Limpopo at two representative sites. We studied how drought patterns are projected to change under future climatic conditions as an important step in identifying adaptation measures (e.g., breeding maize ideotypes resilient to future conditions). Thirty-year time horizons were analyzed, considering three emission scenarios and five global climate models. We applied the WOFOST crop model to simulate maize crop growth and yield formation over South Africa's summer season. We considered three different crop emergence dates. Drought indices indicated that mainly in the scenario SSP5-8.5 (2051-2080), Univen and Syferkuil will experience worsened drought conditions (DC) in the future. Maize yield tends to decline and future changes in the emergence date seem to impact yield significantly. A possible alternative is to delay sowing date to November or December to reduce the potential yield losses. The grain filling period tends to decrease in the future, and a decrease in the duration of the growth cycle is very likely. Combinations of changed sowing time with more drought tolerant maize cultivars having a longer post-anthesis phase will likely reduce the potential negative impact of climate change on maize.

Sea Level and Socioeconomic Uncertainty Drives High-End Coastal Adaptation Costs

Sea-level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing coastal adaptation and impacts are important tools to inform the design of strategies to manage these risks. Representing the often deep uncertainties influencing these risks poses nontrivial challenges. A common uncertainty characterization approach is to use a few benchmark cases to represent the range and relative probabilities of the set of possible outcomes. This has been done in coastal adaptation studies, for example, by using low, moderate, and high percentiles of an input of interest, like sea-level changes. A key consideration is how this simplified characterization of uncertainty influences the distributions of estimated coastal impacts. Here, we show that using only a few benchmark percentiles to represent uncertainty in future sea-level change can lead to overconfident projections and underestimate high-end risks as compared to using full ensembles for sea-level change and socioeconomic parametric uncertainties. When uncertainty in future sea level is characterized by low, moderate, and high percentiles of global mean sea-level rise, estimates of high-end (95th percentile) damages are underestimated by between 18% (SSP1-2.6) and 46% (SSP5-8.5). Additionally, using the 5th and 95th percentiles of sea-level scenarios underestimates the 5%-95% width of the distribution of adaptation costs by a factor ranging from about two to four, depending on SSP-RCP pathway. The resulting underestimation of the uncertainty range in adaptation costs can bias adaptation and mitigation decision-making.

Determining our climate policy future: expert opinions about negative emissions and solar radiation management pathways

Negative emissions technologies and solar radiation management techniques could contribute towards climate stability, either by removing carbon dioxide from the atmosphere and storing it permanently or reflecting sunlight away from the atmosphere. Despite concerns about them, such options are increasingly being discussed as crucial complements to traditional climate change mitigation and adaptation. Expectations around negative emissions and solar radiation management and their associated risks and costs shape public and private discussions of how society deals with the climate crisis. In this study, we rely on a large expert survey (N = 74) to critically examine the future potential of both negative emission options (e.g., carbon dioxide removal) and solar radiation management techniques. We designed a survey process that asked a pool of prominent experts questions about (i) the necessity of adopting negative emissions or solar radiation management options, (ii) the desirability of such options when ranked against each other, (iii) estimations of future efficacy in terms of temperature reductions achieved or gigatons of carbon removed, (iv) expectations about future scaling, commercialization, and deployment targets, and (v) potential risks and barriers. Unlike other elicitation processes where experts are more positive or have high expectations about novel options, our results are more critical and cautionary. We find that some options (notably afforestation and reforestation, ecosystem restoration, and soil carbon sequestration) are envisioned frequently as necessary, desirable, feasible, and affordable, with minimal risks and barriers (compared to other options). This contrasts with other options envisaged as unnecessary risky or costly, notably ocean alkalization or fertilization, space-based reflectors, high-altitude sunshades, and albedo management via clouds. Moreover, only the options of afforestation and reforestation and soil carbon sequestration are expected to be widely deployed before 2035, which raise very real concerns about climate and energy policy in the near- to mid-term.

A functional vulnerability framework for biodiversity conservation

Setting appropriate conservation strategies in a multi-threat world is a challenging goal, especially because of natural complexity and budget limitations that prevent effective management of all ecosystems. Safeguarding the most threatened ecosystems requires accurate and integrative quantification of their vulnerability and their functioning, particularly the potential loss of species trait diversity which imperils their functioning. However, the magnitude of threats and associated biological responses both have high uncertainties. Additionally, a major difficulty is the recurrent lack of reference conditions for a fair and operational measurement of vulnerability. Here, we present a functional vulnerability framework that incorporates uncertainty and reference conditions into a generalizable tool. Through in silico simulations of disturbances, our framework allows us to quantify the vulnerability of communities to a wide range of threats. We demonstrate the relevance and operationality of our framework, and its global, scalable and quantitative comparability, through three case studies on marine fishes and mammals. We show that functional vulnerability has marked geographic and temporal patterns. We underline contrasting contributions of species richness and functional redundancy to the level of vulnerability among case studies, indicating that our integrative assessment can also identify the drivers of vulnerability in a world where uncertainty is omnipresent.

A Soft Magnetoelastic Generator for Wind-Energy Harvesting

The current energy crises and imminent danger of global warming severely limit the ability to scale societal development sustainably. As such, there is a pressing need for utilizing renewable, green energy sources, such as wind energy, which is ubiquitously available on Earth. In this work, a fundamentally new wind-energy-harvesting technology is reported, which is based on the giant magnetoelastic effect in a soft composite system, namely, magnetoelastic generators. Its working principle is based on wind-induced mechanical deformation, which alters the magnetic field in a soft system converting the wind energy into electricity via electromagnetic induction from arbitrary directions. The wind-energy-harvesting system features a low internal impedance of 68 Ω, a high current density of 1.17 mA cm^-2 , and a power density of 0.82 mW cm^-2 under ambient natural wind. The system is capable of sustainably driving small electronics and electrolytically splitting water. The system can generate hydrogen at a rate of 7.5 × 10^-2  mL h^-1 with a wind speed of 20 m s^-1 . Additionally, since magnetic fields can penetrate water molecules, the magnetoelastic generators are intrinsically waterproof and work stably in harsh environments. This work paves a new way for wind-energy harvesting with compelling features, which can contribute largely to the hydrogen economy and the sustainability of human civilization.

A locally relevant framework for assessing the risk of sea level rise under changing temperature conditions: Application in New Caledonia, Pacific Ocean

Sea level rise is a key feature in a warmer world and its impact can be seen globally. Assessing climate change-induced sea level rise, therefore, is urgently needed particularly in small island nations, where the threats of sea level rise are immediate, but the level of preparedness is low. Here, we propose a stochastic simulator to link changes in Mean Annual Temperature (MAT) to Mean Annual Sea Level (MASEL) at the local scale. This is through what-if scenarios that are developed based on the association between local temperature and sea level. The model can provide a basis for a bottom-up impact assessment by addressing limitations of applying large-scale projections in small islands and facilitating the accessibility of the impact assessment to stakeholders. For this purpose, we decompose the MAT and MASEL signals into their linear trend and autocorrelation components as well as independent and identically distributed residual terms. We further explore the association between trend and residual terms of MAT and MASEL. If such dependencies exist, scenarios of sea level can be synthesized based on the trend and residual terms of temperature. We use linear regression to link trends of MAT and MASEL, and copulas to formulate dependencies between residuals. This allows stochastic sampling of MASEL conditioned to trend and random variability in MAT. This framework is used for retrospective and prospective simulations of MASEL in Nouméa, the capital city of New Caledonia, the Pacific. We set up six different model configurations for developing the stochastic sampler, each including various parametric options. By selecting the best setup from each configuration, we provide a multi-model stochastic projection of MASEL, assuming the persistence in current long-term trend in MAT and MASEL. We demonstrate how such simulations can be used for a risk-based impact assessments and discuss sources of uncertainty in future projections.

Human-elephant conflict risk assessment under coupled climatic and anthropogenic changes in Thailand

As natural resources decrease, competition between humans and large endangered wildlife increases, hindering the sustainability of animal conservation and human development. Despite the multi-dimensional nature of such interactions, proactive assessments that consider both the biosphere and anthroposphere remain limited. In this study, we proposed a human elephant conflict risk assessment framework and analyzed the spatial distribution of risk at the baseline (2000-2019) and in the near future (2025-2044) for Thailand, so that it may address the multifaceted characteristics and impending effects of climate change. Future scenarios were based on the combination of RCP45/SSP2 or RCP85/SSP5 and spatial policy, with or without elephant buffer zones. The composite risk index, comprised of hazard, exposure, and vulnerability, was constructed using the geometric mean, and validation was performed with the area under the curve (AUC). Our results projected a shift with increasing future risk toward higher latitudes and altitudes. Increasing future risk (average +1.7% to +7.4%) in the four forest complexes (FCs) in northwestern regions was a result of higher hazard and vulnerability from more favorable habitat conditions and increasing drought probability, respectively. Reduction in future risk (average -3.1% to -57.9%) in other FCs in lower regions was mainly due to decreasing hazard because of decreasing habitat suitability. Our results also highlight geographically explicit strategies to support long-term planning of conservation resources. Areas with increasing future risk are currently facing low conflict; hence it is recommended that future strategies should enhance adaptive capacity and coexistence awareness. Conversely, areas with lowering future risk from a decrease in habitat quality are recommended to identify buffer strategies around protected areas to support existing large elephant populations.

How the future of the global forest sink depends on timber demand, forest management, and carbon policies

Deforestation has contributed significantly to net greenhouse gas emissions, but slowing deforestation, regrowing forests and other ecosystem processes have made forests a net sink. Deforestation will still influence future carbon fluxes, but the role of forest growth through aging, management, and other silvicultural inputs on future carbon fluxes are critically important but not always recognized by bookkeeping and integrated assessment models. When projecting the future, it is vital to capture how management processes affect carbon storage in ecosystems and wood products. This study uses multiple global forest sector models to project forest carbon impacts across 81 shared socioeconomic (SSP) and climate mitigation pathway scenarios. We illustrate the importance of modeling management decisions in existing forests in response to changing demands for land resources, wood products and carbon. Although the models vary in key attributes, there is general agreement across a majority of scenarios that the global forest sector could remain a carbon sink in the future, sequestering 1.2-5.8 GtCO2e/yr over the next century. Carbon fluxes in the baseline scenarios that exclude climate mitigation policy ranged from -0.8 to 4.9 GtCO2e/yr, highlighting the strong influence of SSPs on forest sector model estimates. Improved forest management can jointly increase carbon stocks and harvests without expanding forest area, suggesting that carbon fluxes from managed forests systems deserve more careful consideration by the climate policy community.

A New Integrated Assessment Framework for Climate-Smart Nutrition Security in sub-Saharan Africa: The Integrated Future Estimator for Emissions and Diets (iFEED)

Climate change will put millions more people in Africa at risk of food and nutrition insecurity by 2050. Integrated assessments of food systems tend to be limited by either heavy reliance on models or a lack of information on food and nutrition security. Accordingly, we developed a novel integrated assessment framework that combines models with in-country knowledge and expert academic judgement to explore climate-smart and nutrition-secure food system futures: the integrated Future Estimator for Emissions and Diets (iFEED). Here, we describe iFEED and present its application in Malawi, South Africa, Tanzania and Zambia. The iFEED process begins with a participatory scenario workshop. In-country stakeholders identify two key drivers of food system change, and from these, four possible scenarios are defined. These scenarios provide the underlying narratives of change to the food system. Integrated modeling of climate change, food production and greenhouse gas emissions is then used to explore nutrition security and climate-smart agriculture outcomes for each scenario. Model results are summarized using calibrated statements—quantitative statements of model outcomes and our confidence in them. These include statements about the way in which different trade futures interact with climate change and domestic production in determining nutrition security at the national level. To understand what the model results mean for food systems, the calibrated statements are expanded upon using implication statements. The implications rely on input from a wide range of academic experts—including agro-ecologists and social scientists. A series of workshops are used to incorporate in-country expertise, identifying any gaps in knowledge and summarizing information for country-level recommendations. iFEED stakeholder champions help throughout by providing in-country expertise and disseminating knowledge to policy makers. iFEED has numerous novel aspects that can be used and developed in future work. It provides information to support evidence-based decisions for a climate-smart and nutrition-secure future. In particular, iFEED: (i) employs novel and inclusive reporting of model results and associated in-country food system activities, with comprehensive reporting of uncertainty; (ii) includes climate change mitigation alongside adaptation measures; and (iii) quantifies future population-level nutrition security, as opposed to simply assessing future production and food security implications.

Study protocol: International joint research project ‘climate change resilience of Indigenous socioecological systemsʼ (RISE)

Background

Anthropogenic changes in the environment are increasingly threatening the sustainability of socioecological systems on a global scale. As stewards of the natural capital of over a quarter of the world’s surface area, Indigenous Peoples (IPs), are at the frontline of these changes. Indigenous socioecological systems (ISES) are particularly exposed and sensitive to exogenous changes because of the intimate bounds of IPs with nature. Traditional food systems (TFS) represent one of the most prominent components of ISES, providing not only diverse and nutritious food but also critical socioeconomic, cultural, and spiritual assets. However, a proper understanding of how future climate change may compromise TFS through alterations of related human-nature interactions is still lacking. Climate change resilience of indigenous socioecological systems (RISE) is a new joint international project that aims to fill this gap in knowledge.

Methods and design

RISE will use a comparative case study approach coupling on-site socioeconomic, nutritional, and ecological surveys of the target ISES of Sakha (Republic of Sakha, Russian Federation) and Karen (Kanchanaburi, Thailand) people with statistical models projecting future changes in the distribution and composition of traditional food species under contrasting climate change scenarios. The results presented as alternative narratives of future climate change impacts on TFS will be integrated into a risk assessment framework to explore potential vulnerabilities of ISES operating through altered TFS, and possible adaptation options through stakeholder consultation so that lessons learned can be applied in practice.

Discussion

By undertaking a comprehensive analysis of the socioeconomic and nutritional contributions of TFS toward the sustainability of ISES and projecting future changes under alternative climate change scenarios, RISE is strategically designed to deliver novel and robust science that will contribute towards the integration of Indigenous issues within climate change and sustainable agendas while generating a forum for discussion among Indigenous communities and relevant stakeholders. Its goal is to promote positive co-management and regional development through sustainability and climate change adaptation.

Sea level rise risks and societal adaptation benefits in low-lying coastal areas

Sea level rise (SLR) will increase adaptation needs along low-lying coasts worldwide. Despite centuries of experience with coastal risk, knowledge about the effectiveness and feasibility of societal adaptation on the scale required in a warmer world remains limited. This paper contrasts end-century SLR risks under two warming and two adaptation scenarios, for four coastal settlement archetypes (Urban Atoll Islands, Arctic Communities, Large Tropical Agricultural Deltas, Resource-Rich Cities). We show that adaptation will be substantially beneficial to the continued habitability of most low-lying settlements over this century, at least until the RCP8.5 median SLR level is reached. However, diverse locations worldwide will experience adaptation limits over the course of this century, indicating situations where even ambitious adaptation cannot sufficiently offset a failure to effectively mitigate greenhouse-gas emissions.

Regionally extended shared socioeconomic pathways for the offshore wind industry in Finland

Offshore wind energy is increasingly becoming an important part of European and global low-emission power systems. The aims of this paper are to create a shared understanding on the major drivers of offshore wind development in Finland and to explore how these drivers, and opportunities for the entire industry, may develop over the twenty-first century, under different global futures. This research develops extended shared socioeconomic pathway (SSP) narratives for the offshore wind industry by using a virtual participatory workshop with expert stakeholders. According to our results, the five key drivers shaping the prospects of offshore wind development are public acceptability of offshore energy, global and national demand for low-emission energy, technological development and relative competitiveness of offshore energy, availability of space and wind resources, and energy markets and transmission infrastructure. Nationally extended SSP narratives, building on these key drivers, describe a wide range of alternative future risks and opportunities for developing offshore energy. Under sustainable development (SSP1), offshore wind is likely to soon become a major source of energy in the area, if developed in a balanced manner alongside other uses of the marine space. Under fossil-fuelled development (SSP5), offshore wind grows slower and may experience rapid uptake only in the latter half of the century. Under the regional rivalry scenario (SSP3), the need for local energy sources drives the national energy policies and may create new opportunities for offshore wind. Under the inequality scenario (SSP4), local municipalities and the residents decide on locations of new wind turbines and the overall magnitude of future offshore wind.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40974-022-00252-7.

Making waves in resilience: Drawing lessons from the COVID-19 pandemic for advancing sustainable development

The current COVID-19 pandemic has affected societies across the world while its economic impact has cut deeper than any recession since the Second World War. Climate change is potentially an even more disruptive and complex global challenge. Climate change could cause social and economic damage far larger than that caused by COVID-19. The current pandemic has highlighted the extent to which societies need to prepare for disruptive global environmental crises. Although the dynamics of combating COVID-19 and climate change are different, the priorities for action are the same: behavioral change, international cooperation to manage shared challenges, and technology's role in advancing solutions. For a sustainable recovery from the COVID-19 crisis to be durable and resilient, a return to 'business as usual' and the subsequent often environmentally destructive economic activities must be avoided as they have significantly contributed to climate change. To avoid this, we draw lessons from the experiences of the waves of the COVID-19 pandemic and beyond to advance sustainable development.

Local mortality impacts due to future air pollution under climate change scenarios

The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM_2.5) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM_2.5 levels. PM_2.5 levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM_2.5 linking local population and mortality data with PM_2.5-mortality relationships from the literature, and incorporating population projections under the SSPs. PM_2.5 attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM_2.5 was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM_2.5 attributable burdens mid-century. Our analysis of local PM_2.5 attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM_2.5 mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.

Integrated assessment of localized SSP-RCP narratives for climate change adaptation in coupled human-water systems

The assessment of climate change impacts requires downscaled climate projections and context-specific socioeconomic scenarios. The development of practical climate change adaptation for environmental sustainability at regional and local scales is predicated on a strong understanding of future socio-economic dynamics under a range of potential climate projections. We have addressed this need using integrated assessment of a localized hybrid Shared Socio-economic Pathway - Representative Concentration Pathway (SSP-RCP) framework, through an interdisciplinary and participatory storyline development process that integrates bottom-up local expert-stakeholder knowledge with top-down insights from global SSPs. We use the global SSPs (SSP1 to SSP5) as boundary conditions in conjunction with climate change pathways (RCP4.5, RCP8.5) to create localized SSP narratives in an iterative participatory process, using a storytelling method. By using an integrated socio-economic and environmental system dynamics model developed in collaboration with local stakeholders, we explore the potential impacts of plausible local SSP-RCP narratives and quantify important socio-environmental vulnerabilities of a human-water system (e.g., crop yields, farm income, water security and groundwater depletion) by the mid-century period (i.e., by 2050). The framework is developed to inform climate adaptation for Pakistan's Rechna Doab region, which serves as a representative case of a multi-stakeholder coupled human-water system operating in a developing country. Our results suggest that even under limited socio-economic improvements (e.g., technology, policies, institutions, environmental awareness) water security would be expected to decline and environmental degradation (e.g., groundwater depletion) to worsen. Under RCP 4.5, the average projected increase in water demand in 2030 will be about 7.32% for all SSP scenario narratives, and 10.82% by mid-century. Groundwater use varies significantly across SSPs which results in an average increase of about 29.06% for all SSPs. The proposed framework facilitates the development of future adaptation policies that should consider regional and local planning as well as socio-economic conditions.

Healthy and sustainable diets from today to 2050—The role of international trade

The connection between international trade and food systems (un)sustainability is both contentious and critical for policy work supporting progress towards achieving the twin goals of hunger alleviation and dietary health while improving the overall sustainability of development. We characterize the food system using a set of metrics based upon the EAT-Lancet commission dietary guidelines for both over- and under-consumption of different foods to assess country-level dietary health and sustainability in tandem. Using a partial equilibrium model of agricultural production and trade, we then project the functioning of the global agricultural system to 2050 and calculate the metrics for that year. For most regions we find increased overconsumption above the expert-defined healthy and sustainable diet thresholds, with more limited progress towards closing dietary health and sustainability gaps where they currently exist. Trade influences this dynamic into the future under certain socioeconomic conditions, and we find that under a “business as usual” trade environment, future agricultural import profiles continue to be misaligned with dietary health and sustainability outcomes, suggesting the potential for early intervention in trade policy as a means to positively influence food system outcomes.

Evaluation of historical CMIP6 model simulations and future projections of temperature over the Pan-Third Pole region

The Pan-Third Pole (PTP) region, which encompasses the Eurasian highlands and their surroundings, has experienced unprecedented, accelerated warming during the past decades. This study evaluates the performance of historical simulation runs of the Coupled Model Intercomparison Project (CMIP6) in capturing spatial patterns and temporal variations observed over the PTP region for mean and extreme temperatures. In addition, projected changes in temperatures under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are also reported. Four indices were used to characterize changes in temperature extremes: the annual maximum value of daily maximum temperature (TXx), the annual minimum value of daily minimum temperature (TNn), and indices for the percentage of warm days (TX90p) and warm nights (TN90p). Results indicate that most CMIP6 models generally capture the characteristics of the observed mean and extreme temperatures over the PTP region, but there still are slight cold biases in the Tibetan Plateau. Future changes of mean and extreme temperatures demonstrate that a strong increase will occur for the entire PTP region during the twenty-first century under all four SSP scenarios. Between 2015 and 2099, ensemble area-averaged annual mean temperatures are projected to increase by 1.24 °C/100 year, 3.28 °C/100 year, 5.57 °C/100 year, and 7.40 °C/100 year for the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios, respectively. For TXx and TNn, the most intense warming is projected in Central Asia. The greatest number of projected TX90p and TN90p will occur in the Southeast Asia and Tibetan Plateau, respectively.

Evaluating pollution damage function through carbon pricing, renewable energy demand, and cleaner technologies in China: blue versus green economy

Climate change and increased greenhouse gas emissions boost the global average temperature to less than 2°C, which is the estimated breakeven point. The globe is moving into blue pollution economies as the environmental sustainability objective becomes more distorted. The study looked at three United Nations Sustainable Development Goals, namely (i) affordable and clean energy; (ii) industry, innovation, and infrastructure; and (iii) climate change, to see how far the Chinese economy has progressed toward green and clean development strategy. In the context of China, the "pollution damage function" was intended to refer to carbon damages related to carbon pricing, technological variables, sustained economic growth, incoming foreign investment, and green energy. The data was collected between 1975 and 2019 and analyzed using various statistical approaches. The results of the autoregressive distributed lag model suggest that carbon taxes on industrial emissions reduce carbon damages in the short and long run. Furthermore, a rise in inbound foreign investment and renewable energy demand reduces carbon damages in the short term, proving the "pollution halo" and "green energy" hypotheses; nonetheless, the results are insufficient to explain the stated results in the long run. In the long run, technology transfers and continued economic growth are beneficial in reducing carbon damages and confirming the potential of cleaner solutions in pollution mitigation. The causal inferences show the one-way relationship running from carbon pricing and technology transfer to carbon damages, and green energy to high-technology exports in a country. The impulse response estimates suggested that carbon tax, inbound foreign investment, and technology transfers likely decrease carbon damages for the next 10 years. On the other hand, continued economic growth and inadequate green energy sources are likely to increase carbon pollution in a country. The variance decomposition analysis suggested that carbon pricing and information and communication technology exports would likely significantly influence carbon damages over time. To keep the earth's temperature within the set threshold, the true motivation to shift from a blue to a green economy required strict environmental legislation, the use of green energy sources, and the export of cleaner technologies. Source: Authors' self-extract.

The Impact of Green Investment and Green Marketing on Business Performance: The Mediation Role of Corporate Social Responsibility in Ethiopia’s Chinese Textile Companies

In the current era of rapidly increasing industrialization and rising environmental concerns, green investment and green marketing have become hot strategic issues to improve the business performance of companies. This study aims to examine the impact of green marketing and green investment on business performance using the mediating role of corporate social responsibility (CSR) in Ethiopia’s Chinese textile companies. The study used a mixed research method approach that included primary and secondary data sources, with the required data gathered from 237 respondents in Ethiopia’s Chinese textile companies. The employed research data were analyzed using a structural equation model (SEM) and multivariate regression analysis to identify the causal relationship between green investment, green marketing, and business performance. The main result reveals that green marketing and green investment positively and substantially influence a firm’s business performance. Furthermore, results show that CSR has positively and significantly mediated the impact of green investment and green marketing on business performance. Even though Chinese textile companies in Ethiopia have started to incorporate green investment, green marketing, and CSR into their operations, the government and Chinese businesses should work together to close the gaps that prevent long-term growth. This study provides a useful model to help companies, managers, practitioners, and policymakers understand and manage green marketing, investment, and CSR to improve business performance.

Probabilistic projections of baseline twenty-first century CO2 emissions using a simple calibrated integrated assessment model

Probabilistic projections of baseline (with no additional mitigation policies) future carbon emissions are important for sound climate risk assessments. Deep uncertainty surrounds many drivers of projected emissions. Here, we use a simple integrated assessment model, calibrated to century-scale data and expert assessments of baseline emissions, global economic growth, and population growth, to make probabilistic projections of carbon emissions through 2100. Under a variety of assumptions about fossil fuel resource levels and decarbonization rates, our projections largely agree with several emissions projections under current policy conditions. Our global sensitivity analysis identifies several key economic drivers of uncertainty in future emissions and shows important higher-level interactions between economic and technological parameters, while population uncertainties are less important. Our analysis also projects relatively low global economic growth rates over the remainder of the century. This illustrates the importance of additional research into economic growth dynamics for climate risk assessment, especially if pledged and future climate mitigation policies are weakened or have delayed implementations. These results showcase the power of using a simple, transparent, and calibrated model. While the simple model structure has several advantages, it also creates caveats for our results which are related to important areas for further research.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10584-021-03279-7.

Research Trends on Climate Change and Circular Economy from a Knowledge Mapping Perspective

The circular economy (CE) has been proposed as a potentially significant catalyst to enhance the current response to the global climate crisis. The objective of this study was to investigate the scientific literature of the research between climate change and CE adopting a knowledge mapping approach. Based on a total of 789 peer-reviewed publications extracted from Scopus, we found that research on climate change and CE is continually growing and interdisciplinary in nature. Europe notably leads scientific production. Keyword evolution shows that CE has been influenced by more lines of research than climate change. We also found that waste management is the CE approach most associated with climate change, mitigation is the climate action most impacted by CE, and food is the most reported greenhouse gas (GHG)-emitting material. However, there are knowledge gaps in the integration of the social dimension, the promotion of climate change adaptation, and the association of sustainable development goal (SDG) 13. Finally, we identified four potentially valuable directions for future studies: (i) CE practices, (ii) bioeconomy, (iii) climate and energy, and (iv) sustainability and natural resources, in which carbon recovery technologies, green materials, regional supply chains, circular agriculture models, and nature-based solutions are promising themes.

Climate change research and action must look beyond 2100

Anthropogenic activity is changing Earth's climate and ecosystems in ways that are potentially dangerous and disruptive to humans. Greenhouse gas concentrations in the atmosphere continue to rise, ensuring that these changes will be felt for centuries beyond 2100, the current benchmark for projection. Estimating the effects of past, current, and potential future emissions to only 2100 is therefore short-sighted. Critical problems for food production and climate-forced human migration are projected to arise well before 2100, raising questions regarding the habitability of some regions of the Earth after the turn of the century. To highlight the need for more distant horizon scanning, we model climate change to 2500 under a suite of emission scenarios and quantify associated projections of crop viability and heat stress. Together, our projections show global climate impacts increase significantly after 2100 without rapid mitigation. As a result, we argue that projections of climate and its effects on human well-being and associated governance and policy must be framed beyond 2100.

Deep mitigation of CO2 and non-CO2 greenhouse gases toward 1.5 °C and 2 °C futures

Stabilizing climate change well below 2 °C and towards 1.5 °C requires comprehensive mitigation of all greenhouse gases (GHG), including both CO₂ and non-CO₂ GHG emissions. Here we incorporate the latest global non-CO₂ emissions and mitigation data into a state-of-the-art integrated assessment model GCAM and examine 90 mitigation scenarios pairing different levels of CO₂ and non-CO₂ GHG abatement pathways. We estimate that when non-CO₂ mitigation contributions are not fully implemented, the timing of net-zero CO₂ must occur about two decades earlier. Conversely, comprehensive GHG abatement that fully integrates non-CO₂ mitigation measures in addition to a net-zero CO₂ commitment can help achieve 1.5 °C stabilization. While decarbonization-driven fuel switching mainly reduces non-CO₂ emissions from fuel extraction and end use, targeted non-CO₂ mitigation measures can significantly reduce fluorinated gas emissions from industrial processes and cooling sectors. Our integrated modeling provides direct insights in how system-wide all GHG mitigation can affect the timing of net-zero CO₂ for 1.5 °C and 2 °C climate change scenarios.

Managing the financial risks of climate change and pandemics: What we know (and don't know)

The COVID-19 pandemic is generating the largest shock in the global economy since 1929. Although the pandemic has been unprecedented in scale and type, such complex, compounding shocks are not uncommon and are more likely in our modern, interconnected world. Our ability to assess and anticipate compounding risks is limited. Here, we propose a framework for assessing the economic losses associated with compounding climate, economic, and pandemic shocks. We propose a new metric, the compound risk multiplier, to measure the scale of the amplification effect and find that this can peak at over 150%; that is, the GDP impacts of the compound shock can be 50% larger than the sum of the individual shocks. Our results suggest that ignoring compounding risks could be a major blindspot in our ability to prepare for future crises. This underlines the urgency of accounting for compounding shocks within financial, fiscal, and crisis risk management.