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Pesticide use is a crucial human-driven change in the Anthropocene that negatively impacts the environment and ecosystems. While pesticides are essential to agriculture to sustain crop production and ensure global food security, they also lead to significant environmental impacts. The export of pesticides after application from the agricultural fields threatens the soil, groundwater and surface water quality in many world regions. Pesticide use is constantly increasing globally, driven mainly by agricultural intensification, despite stricter regulations and higher pesticide effectiveness. To enhance the understanding of future pesticide use and emissions and make informed farm-to-policy decisions, we developed Pesticide Agricultural Shared Socio-Economic Pathways (Pest-Agri-SSPs) in six steps. The Pest-Agri-SSPs are based on an extensive literature review and expert knowledge, considering significant climate and socio-economic drivers from farm to continental scale in combination with multiple actors impacting them. In the literature, pesticide use is associated with farmer behaviour and agricultural practices, pest damage, technique and efficiency of pesticide application, agricultural policy and demand for agricultural products. Here, we developed Pest-Agri-SSPs upon this understanding of pesticide use drivers and relating them to plausible sectoral developments, as described by the Shared Socio-economic Pathways for European agriculture and food systems (Eur-Agri-SSPs). The Pest-Agri-SSPs present European pesticide use in five scenarios with low to high challenges to climate change adaptation and mitigation up to 2050. The most sustainable scenario (Pest-Agri-SSP1) shows a decrease in pesticide use owing to sustainable agricultural practices, technological advances and a pro-environmental orientation of agricultural policies. On the contrary, the Pest-Agri-SSP3 and Pest-Agri-SSP4 show an increase in pesticide use resulting from high challenges from pest pressure, resource depletion and relaxed agricultural policies. Pest-Agri-SSP2 presents a stabilised pesticide use resulting from strict policies and slow transitions by farmers to sustainable agricultural practices. Pest-Agri-SSP5 shows a decrease in pesticide use for most drivers, influenced mainly by rapid technological development and the application of sustainable agricultural practices. However, Pest-Agri-SSP5 also shows a relatively low rise in pesticide use driven by agricultural demand, production, and climate change. Our results highlight the need for a holistic approach to tackle pesticide use and emissions, considering the identified drivers and future developments. The storylines and qualitative assessment provide a platform to make quantitative assumptions for numerical modelling and evaluating policy targets. Keywords: Farm characteristics, pest damage, technology, policy, socioeconomic, agriculture and food systems Adapted version of this work has been submitted to Journal of Environmental Management: Nagesh P, Edelenbosch OY , Dekker SC, de Boer HJ, Mitter H, van Vuuren DP. Pesticide use under the influence of socio-economic and climate change: Pest-Agri-SSPs

The expert group on scenarios and models of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services initiated the development of the Nature Futures Framework for developing scenarios of positive futures for nature, to help inform assessments of policy options. This new scenarios and modelling Framework seeks to open up diversity and plurality of perspectives by differentiating three main value perspectives on nature – Nature for Nature (intrinsic values of nature), Nature for Society (instrumental values) and Nature as Culture (relational values). This paper describes how the Nature Futures Framework can be applied in modelling to support policy processes by identifying key interventions for change in realizing a diversity of desirable futures. First, the paper introduces and elaborates on key building blocks of the framework for developing qualitative scenarios and translating them into quantitative scenarios: i) multiple value perspectives on nature and the Nature Futures frontier representing diverse preferences, ii) incorporating mutual and key feedbacks of social-ecological systems in Nature Futures scenarios, and iii) indicators describing the evolution of social-ecological systems with complementary knowledge and data. This paper then presents three possible application approaches to modelling Nature Futures scenarios to support the i) review, ii) implementation and iii) design phases of policy processes. The main objective of this paper is to facilitate the integration of the relational values of nature in models, through improved indicators and other forms of evidence, and to strengthen modelled linkages across biodiversity, ecosystems, nature’s contributions to people, and quality of life to identify science- and knowledge-based interventions and to enhance ecological understanding for achieving sustainable futures. The paper aims at stimulating the development of new scenarios and models based on this new framework by a wide community of modelers, and the testing and possible further development of the framework, particularly in the context of future IPBES assessments.

The role of soil organic carbon (SOC) sequestration as a ‘win-win’ solution to both climate change and food insecurity receives an increasing promotion. The opportunity may be too good to be missed! Yet the tremendous complexity of the two issues at stake calls for a detailed and nuanced examination of any potential solution, no matter how appealing. Here, we critically re-examine the benefits of global SOC sequestration strategies on both climate change mitigation and food production. While estimated contributions of SOC sequestration to climate change vary, almost none take SOC saturation into account. Here, we show that including saturation in estimations decreases any potential contribution of SOC sequestration to climate change mitigation by 53%–81% towards 2100. In addition, reviewing more than 21 meta-analyses, we found that observed yield effects of increasing SOC are inconsistent, ranging from negative to neutral to positive. We find that the promise of a win-win outcome is confirmed only when specific land management practices are applied under specific conditions. Therefore, we argue that the existing knowledge base does not justify the current trend to set global agendas focusing first and foremost on SOC sequestration. Away from climate-smart soils, we need a shift towards soil-smart agriculture, adaptative and adapted to each local context, and where multiple soil functions are quantified concurrently. Only such comprehensive assessments will allow synergies for land sustainability to be maximised and agronomic requirements for food security to be fulfilled. This implies moving away from global targets for SOC in agricultural soils. SOC sequestration may occur along this pathway and contribute to climate change mitigation and should be regarded as a co-benefit.

National-level climate actions will be vital in achieving global temperature goals in the coming decades. Near-term (2025–2030) plans are laid out in Nationally Determined Contributions; the next step is the submission of long-term strategies for 2050. At present, national scenarios underpinning long-term strategies are poorly coordinated and incompatible across countries, preventing assessment of individual nations’ climate policies. Here we present a systematic and standardized, yet flexible, scenario framework varying 2050 emissions to build long-term national energy and climate mitigation scenarios. Applying the framework to six major Asian countries reveals individual challenges in energy system transformation and investment needs in comparable scenarios. This framework could be a starting point for comprehensive assessments as input to the Global Stocktake over the coming years., 世界各国の2050年の温室効果ガス削減目標を分析するための国際的な研究フレームワークの提案. 京都大学プレスリリース. 2021-05-28., Pathways to global climate targets. 京都大学プレスリリース. 2021-06-01.

Previous studies have projected a significant role for bioenergy in decarbonizing the global economy and helping realize international climate goals such as limiting global average warming to 2 ˚C or 1.5 ˚C. However, with substantial variability in bioenergy results and significant concerns about potential environmental and social implications, greater transparency and dedicated assessment of the underlying modeling and results and more detailed understanding of the potential role of bioenergy are needed. Stanford University’s Energy Modeling Forum (EMF) initiated a 33rd study (EMF-33) to explore the viability of large-scale bioenergy as part of a comprehensive climate management strategy. This special issue presents the papers of the EMF-33 study—a multi-year inter-model comparison project designed to understand and assess global, long-run biomass supply and bioenergy deployment potentials and related uncertainties. Using a novel scenario design with independent biomass supply and bioenergy demand protocols, EMF-33 separately elucidates and explores the modeling of biomass feedstock supplies and bioenergy technologies and their deployment—revealing, comparing, and assessing the modeling that is suggesting that bioenergy could be a key climate containment strategy. This introduction provides an overview of the EMF-33 study design and the overview, thematic, and individual modeling team papers and types of insights that make up this special issue. By providing enhanced transparency and new detailed insights, we hope to inform policy dialogue about the potential role of bioenergy and facilitate new research.

Limiting global warming to 2°C or less compared with pre-industrial temperatures will require unprecedented rates of decarbonization globally. The scale and scope of transformational change required across sectors and actors in society raises critical questions of feasibility. Much of the literature on mitigation pathways addresses technological and economic aspects of feasibility, but overlooks the behavioral, cultural, and social factors that affect theoretical and practical mitigation pathways. We present a tripartite framework that “unpacks” the concept of mitigation pathways by distinguishing three factors that together determine actual mitigation: technical potential, initiative feasibility, and behavioral plasticity. The framework aims to integrate and streamline heterogeneous disciplinary research traditions toward a more comprehensive and transparent approach that will facilitate learning across disciplines and enable mitigation pathways to more fully reflect available knowledge. We offer three suggestions for integrating the tripartite framework into current research on climate change mitigation. Most research on pathways to mitigating climate change has concentrated on technological and economic aspects of feasibility with limited consideration of the behavioral, cultural, and social factors that also affect the feasibility of mitigation. In this Perspective, we present a tripartite framework that “unpacks” the concept of mitigation pathways by distinguishing three factors that together determine actual mitigation: technical potential, initiative feasibility, and behavioral plasticity. We offer suggestions for integrating the tripartite framework into current research on climate change mitigation.

Summary To halt climate change this century, we must reduce carbon dioxide (CO2) emissions from human activities to net zero. Any emission sources, such as in the energy or land-use sectors, must be balanced by natural or technological carbon sinks that facilitate CO2 removal (CDR) from the atmosphere. Projections of demand for large-scale CDR are based on an integrated scenario framework for emission scenarios composed of emission profiles as well as alternative socio-economic development trends and social values consistent with them. The framework, however, was developed years before systematic reviews of CDR entered the literature. This primer provides an overview of the purposes of scenarios in climate-change research and how they are used. It also introduces the integrated scenario framework and why it came about. CDR studies using the scenario framework, as well as its limitations, are discussed. Possible future developments for the scenario framework are highlighted, especially in relation to CDR., To halt climate change, we must reduce anthropogenic CO2 emissions to net zero. Any emission sources must be balanced by natural or technological carbon sinks that facilitate CO2 removal (CDR) from the atmosphere. The integrated scenario framework represents how socio-economic trends and social values interact with biophysical systems in exploring future climate change and decarbonization pathways. This primer introduces the integrated scenario framework and its application to explore options for offsetting emissions with CDR.

Plastics show the strongest production growth of all bulk materials and are already responsible for 4.5% of global greenhouse gas emissions

To predict how society and political systems might actually respond to warming, upgrade integrated assessment models. To predict how society and political systems might actually respond to warming, upgrade integrated assessment models.

Delaying climate mitigation action and allowing a temporary overshoot of temperature targets require large-scale carbon dioxide removal (CDR) in the second half of this century that may induce adverse side effects on land, food and ecosystems. Meanwhile, meeting climate goals without global net-negative emissions inevitably needs early and rapid emission reduction measures, which also brings challenges in the near term. Here we identify the implications for land-use and food systems of scenarios that do not depend on land-based CDR technologies. We find that early climate action has multiple benefits and trade-offs, and avoids the need for drastic (mitigation-induced) shifts in land use in the long term. Further long-term benefits are lower food prices, reduced risk of hunger and lower demand for irrigation water. Simultaneously, however, near-term mitigation pressures in the agriculture, forest and land-use sector and the required land area for energy crops increase, resulting in additional risk of food insecurity.

This study examines model-specific assumptions and projections of methane (CH4) emissions in deep mitigation scenarios generated by integrated assessment models (IAMs). For this, scenarios of nine models are compared in terms of sectoral and regional CH4emission reduction strategies, as well as resulting climate impacts. The models’ projected reduction potentials are compared to sector and technology-specific reduction potentials found in literature. Significant cost-effective and non-climate policy related reductions are projected in the reference case (10–36% compared to a “frozen emission factor” scenario in 2100). Still, compared to 2010, CH4emissions are expected to rise steadily by 9–72% (up to 412 to 654 Mt CH4/year). Ambitious CO2reduction measures could by themselves lead to a reduction of CH4emissions due to a reduction of fossil fuels (22–48% compared to the reference case in 2100). However, direct CH4mitigation is crucial and more effective in bringing down CH4(50–74% compared to the reference case). Given the limited reduction potential, agriculture CH4emissions are projected to constitute an increasingly larger share of total anthropogenic CH4emissions in mitigation scenarios. Enteric fermentation in ruminants is in that respect by far the largest mitigation bottleneck later in the century with a projected 40–78% of total remaining CH4emissions in 2100 in a strong (2 °C) climate policy case.

The Paris Agreement does not only stipulate to limit the global average temperature increase to well below 2 °C, it also calls for ‘making finance flows consistent with a pathway towards low greenhouse gas emissions’. Consequently, there is an urgent need to understand the implications of climate targets for energy systems and quantify the associated investment requirements in the coming decade. A meaningful analysis must however consider the near-term mitigation requirements to avoid the overshoot of a temperature goal. It must also include the recently observed fast technological progress in key mitigation options. Here, we use a new and unique scenario ensemble that limit peak warming by construction and that stems from seven up-to-date integrated assessment models. This allows us to study the near-term implications of different limits to peak temperature increase under a consistent and up-to-date set of assumptions. We find that ambitious immediate action allows for limiting median warming outcomes to well below 2 °C in all models. By contrast, current nationally determined contributions for 2030 would add around 0.2 °C of peak warming, leading to an unavoidable transgression of 1.5 °C in all models, and 2 °C in some. In contrast to the incremental changes as foreseen by current plans, ambitious peak warming targets require decisive emission cuts until 2030, with the most substantial contribution to decarbonization coming from the power sector. Therefore, investments into low-carbon power generation need to increase beyond current levels to meet the Paris goals, especially for solar and wind technologies and related system enhancements for electricity transmission, distribution and storage. Estimates on absolute investment levels, up-scaling of other low-carbon power generation technologies and investment shares in less ambitious scenarios vary considerably across models. In scenarios limiting peak warming to below 2 °C, while coal is phased out quickly, oil and gas are still being used significantly until 2030, albeit at lower than current levels. This requires continued investments into existing oil and gas infrastructure, but investments into new fields in such scenarios might not be needed. The results show that credible and effective policy action is essential for ensuring efficient allocation of investments aligned with medium-term climate targets.

Process-based integrated assessment models (IAMs) project long-term transformation pathways in energy and land-use systems under what-if assumptions. IAM evaluation is necessary to improve the models’ usefulness as scientific tools applicable in the complex and contested domain of climate change mitigation. We contribute the first comprehensive synthesis of process-based IAM evaluation research, drawing on a wide range of examples across six different evaluation methods including historical simulations, stylised facts, and model diagnostics. For each evaluation method, we identify progress and milestones to date, and draw out lessons learnt as well as challenges remaining. We find that each evaluation method has distinctive strengths, as well as constraints on its application. We use these insights to propose a systematic evaluation framework combining multiple methods to establish the appropriateness, interpretability, credibility, and relevance of process-based IAMs as useful scientific tools for informing climate policy. We also set out a programme of evaluation research to be mainstreamed both within and outside the IAM community.

Integrated assessment models (IAMs) form a prime tool in informing about climate mitigation strategies. Diagnostic indicators that allow comparison across these models can help describe and explain differences in model projections. This increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler (2015 Technol. Forecast. Soc. Change 90 45–61)). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, to systematically and routinely assess IAM behaviour, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index, emission reduction type index, inertia timescale, fossil fuel reduction, transformation index and cost per abatement value. We apply the approach to 17 IAMs, assessing both older as well as their latest versions, as applied in the IPCC 6th Assessment Report. The study shows that the approach can be easily applied and used to indentify key differences between models and model versions. Moreover, we demonstrate that this comparison helps to link model behavior to model characteristics and assumptions. We show that together, the set of six indicators can provide useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend.

Suitability maps for solar photovoltaic (PV) parks are key in estimating potential supply of these resources. These maps are typically created based on expert judgement using variables such as resource availability (irradiation), topography (e.g. slope), socio-economic factors (e.g. distance to urban areas), infrastructure (e.g. distance to roads and transmission lines), land cover type, and / or ecological functions (e.g. protected areas). However, such priori expert-based suitability maps do not necessarily match up with the actual spatial distribution of solar PV or wind parks. Here we aim to understand the determinants of the actual global distribution of solar PV parks by relating the locations of utility-scale solar PV parks worldwide to the above-mentioned variables. Specifically, we develop a generalized linear mixed-effects model to predict the probability of occurrence of a PV park at a certain location, based on variable values at each PV location as well as randomly selected locations where PV parks are absent. We furthermore include country as random effect to take into account inter-country differences in renewable energy policies. We then use the model to create a global 1km resolution map of the likelihood of finding a solar PV park and identify the most important determinants of their distribution. Finally, we compare our findings to the suitability maps currently used by the integrated assessment model IMAGE, which are based on expert judgement using land cover, ecological functions, infrastructure, socio-economic factors and topography. From this comparison and our identification of the most important determinants, we can deduce what drives geographical patterns in the actual distribution of renewable energy facilities, which can be used to improve suitability maps in future integrated assessments of the energy transition.

Closing the remaining emissions gap between Nationally Determined Contributions (NDCs) and the global emissions levels needed to achieve the Paris Agreement’s climate goals will likely require a comprehensive package of policy measures. National and sectoral policies can help fill the gap, but success stories in one country cannot be automatically replicated in other countries, but need to be adapted to the local context. Here, we develop a new Bridge scenario based on nationally relevant measures informed by interactions with country experts. We implement this scenario with an ensemble of global integrated assessment models (IAMs). We show that a global roll-out of these good practice policies closes the emissions gap between current NDCs and a cost-optimal well below 2 °C scenario by two thirds by 2030 and more than fully by 2050, while being less disruptive than a scenario that delays cost-optimal mitigation to 2030. The Bridge scenario leads to a scale-up of renewable energy (reaching 50%-85% of global electricity supply by 2050), electrification of end-uses, efficiency improvements in energy demand sectors, and enhanced afforestation and reforestation. Our analysis suggests that early action via good-practice policies is less costly than a delay in global climate cooperation.

Global emissions scenarios play a critical role in the assessment of strategies to mitigate climate change and their related societal transformations. The current generation of scenarios, however, are criticized because they rely heavily on net negative CO2 emissions (NNCE) that result from allowing temperature limits to be temporarily exceeded. In this study we present a new set of emissions scenarios that exclude NNCE. We show that such scenarios require a more rapid near-term transformation with significant long-term gains for the economy (even without considering the benefits of avoided climate impacts). Scenarios that avoid temperature overshoot and NNCE are thus not only economically more attractive over the long term, they also involve lower climate risks. Our study further identifies possible alternative configurations of net-zero CO2 emissions systems and the distinct roles of different sectors and regions in order to balance emissions sources and sinks.

Water is an essential resource for human life and the environment. The widespread use of chemicals in daily life has led to significant water quality concerns. During the production phase, the use phase as well as after use, (residues of) these chemicals can enter the environment and water systems. Furthermore, the use and production of chemicals are increasing rapidly, driven by mainly population growth, urbanisation and economic growth. Increased use leads to further emissions of chemicals to water, posing significant water quality concerns. Henceforth there is an urgent need to understand the linkage between society and production and consumption of chemicals to explore possible changes in water quality.Socio-economic scenario analysis is a useful tool to investigate the long-term consequences of future change and mitigation options. While scenarios have been broadly applied to understand air pollution, this not yet the case for chemical pollution to surface waters. In this work, we propose a general framework to develop scenarios for the future emissions of chemicals to water by using the Shared Socio-economic Pathways (SSP). The framework follows the basic elements of the scenario development process by defining the current system, describe the changes in emissions with scenario drivers and elaboration to the future. The framework is then tested on a set of selected ‘example’ chemicals that represent broader chemical groups of pharmaceuticals (Ibuprofen and Diclofenac), pesticides (Terbuthylazine) and industrial chemicals (Cadmium and Di-ethyl phthalate). Chemical emissions to water over the past years were used to understand their yearly trends and patterns over the European countries. Lastly, the emission scenarios for chemicals for 2050 were developed by using SSP drivers from the IMAGE Integrated assessment model as an input to the empirical emission models. The three SSP scenarios: SSP1 ("Sustainability"), SSP2 ("Middle of the Road") and SSP3 ("Regional Rivalry") focusing on Europe were included. Additionally, the developed scenarios also describe mitigation efforts.The results of emission scenarios displayed an increase in emissions up to 2050 for the exemplary chemicals in Western Europe for all three scenarios SSP1, SSP2 and SSP3. While the emissions of chemicals linearly decreased in Eastern Europe for the same period. SSP3 showed the highest emissions in 2050 except for cadmium emissions from wastewater treatment plants. The results showed that the framework helps in understanding the possible influence of socio-economic changes on use and emissions of chemicals which can be a part of future risk assessments. While the framework can be extended similarly to other pharmaceuticals and pesticides, it requires a detailed understanding of complex emission sources for industrial chemicals.

Low-carbon pathways consistent with the 2 °C and 1.5 °C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.

Several studies have shown that the greenhouse gas reduction resulting from the current nationally determined contributions (NDCs) will not be enough to meet the overall targets of the Paris Climate Agreement. It has been suggested that more ambition mitigations of short-lived climate forcer (SLCF) emissions could potentially be a way to reduce the risk of overshooting the 1.5 or 2 °C target in a cost-effective way. In this study, we employ eight state-of-the-art integrated assessment models (IAMs) to examine the global temperature effects of ambitious reductions of methane, black and organic carbon, and hydrofluorocarbon emissions. The SLCFs measures considered are found to add significantly to the effect of the NDCs on short-term global mean temperature (GMT) (in the year 2040: − 0.03 to − 0.15 °C) and on reducing the short-term rate-of-change (by − 2 to 15%), but only a small effect on reducing the maximum temperature change before 2100. This, because later in the century under assumed ambitious climate policy, SLCF mitigation is maximized, either directly or indirectly due to changes in the energy system. All three SLCF groups can contribute to achieving GMT changes.