Global food efficiency of climate change mitigation in agriculture

Concerns exist regarding potential trade-offs between climate change mitigation in agriculture and food security. Against this background, the Global Biosphere Management Model (GLOBIOM) is applied to a range of scenarios of mitigation of emissions from agriculture to assess the implications of climate mitigation for agricultural production, prices and food availability. The " food efficiency of mitigation " (FEM) is introduced as a tool to make statements about how to attain desired levels of agricultural mitigation in the most efficient manner in terms of food security. It is applied to a range of policy scenarios which contrast a climate policy regime with full global collaboration to scenarios of fragmented climate policies that grant exemptions to selected developing country groups. Results indicate increasing marginal costs of abatement in terms of food calories and suggest that agricultural mitigation is most food efficient in a policy regime with global collaboration. Exemptions from this regime cause food efficiency losses

Energy Sector Adaptation in Response to Water Scarcity

Integrated assessment models (IAMs) have largely ignored the impacts of water scarcity on the energy sector and the related implications for climate change mitigation. However, significant water is required in the production of energy, including for thermoelectric power plant cooling, hydropower generation, irrigation for bioenergy, and the extraction and refining of liquid fuels. With a changing climate and expectations of increasing competition for water from the agricultural and municipal sectors, it is unclear whether sufficient water will be available where needed to support water-intensive energy technologies (e.g., thermoelectric generation) in the future. Thus, it is important that water use and water constraints are incorporated into IAMs to better understand energy sector adaptation to water scarcity. The MESSAGE model has recently been updated with the capability to quantify the water consumption and withdrawal requirements of the energy sector and now includes several cooling technologies for addressing water scarcity. These new capabilities have been used to quantify water consumption, water withdrawal, and thermal pollution associated with pre-existing climate change mitigation scenarios. The current study takes the next step by introducing water constraints into Shared Socioeconomic Pathway (SSP) scenarios to examine whether and how the energy sector can adapt to water scarcity. This study will provide insight into the following questions related to energy sector adaptation to water scarcity: How does the energy sector adapt to water scarcity in different regions? What are the costs associated with adaptation to water scarcity? How do adaptations to constraints on water withdrawal and consumption differ? Is climate mitigation limited under water scarcity (esp. with low deployment of wind/ solar)? How important are dry cooling and seawater cooling for addressing water scarcity and climate mitigation

Energy sector water use implications of a 2°C climate policy

Quantifying water implications of energy transitions is important for assessing long-term freshwater sustainability since large volumes of water are currently used throughout the energy sector. In this paper, we assess direct global energy sector water use and thermal water pollution across a broad range of energy system transformation pathways to assess water impacts of a 2 °C climate policy. A global integrated assessment model is equipped with the capabilities to account for the water impacts of technologies located throughout the energy supply chain. The model framework is applied across a broad range of 2 °C scenarios to highlight long-term water impact uncertainties over the 21st century. We find that water implications vary significantly across scenarios, and that adaptation in power plant cooling technology can considerably reduce global freshwater withdrawals and thermal pollution. Global freshwater consumption increases across all of the investigated 2 °C scenarios as a result of rapidly expanding electricity demand in developing regions and the prevalence of freshwater-cooled thermal power generation. Reducing energy demand emerges as a robust strategy for water conservation, and enables increased technological flexibility on the supply side to fulfill ambitious climate objectives. The results underscore the importance of an integrated approach when developing water, energy, and climate policy, especially in regions where rapid growth in both energy and water demands is anticipated

Energy Sector Adaptation in Response to Water Scarcity

Integrated assessment models (IAMs) have largely ignored the impacts of water scarcity on the energy sector and the related implications for climate change mitigation. However, significant water is required in the production of energy, including for thermoelectric power plant cooling, hydropower generation, irrigation for bioenergy, and the extraction and refining of liquid fuels. With a changing climate and expectations of increasing competition for water from the agricultural and municipal sectors, it is unclear whether sufficient water will be available where needed to support water-intensive energy technologies (e.g., thermoelectric generation) in the future. Thus, it is important that water use and water constraints are incorporated into IAMs to better understand energy sector adaptation to water scarcity. The MESSAGE model has recently been updated with the capability to quantify the water consumption and withdrawal requirements of the energy sector and now includes several cooling technologies for addressing water scarcity. These new capabilities have been used to quantify water consumption, water withdrawal, and thermal pollution associated with pre-existing climate change mitigation scenarios. The current study takes the next step by introducing water constraints into Shared Socioeconomic Pathway (SSP) scenarios to examine whether and how the energy sector can adapt to water scarcity. This study will provide insight into the following questions related to energy sector adaptation to water scarcity: How does the energy sector adapt to water scarcity in different regions? What are the costs associated with adaptation to water scarcity? How do adaptations to constraints on water withdrawal and consumption differ? Is climate mitigation limited under water scarcity (esp. with low deployment of wind/ solar)? How important are dry cooling and seawater cooling for addressing water scarcity and climate mitigation

Understanding the origin of Paris Agreement emission uncertainties

The UN Paris Agreement puts in place a legally binding mechanism to increase mitigation action over time. Countries put forward pledges called nationally determined contributions (NDC) whose impact is assessed in global stocktaking exercises. Subsequently, actions can then be strengthened in light of the Paris climate objective: Limiting global mean temperature increase to well below 2 °C and pursuing efforts to limit it further to 1.5 °C. However, pledged actions are currently described ambiguously and this complicates the global stocktaking exercise. Here, we systematically explore possible interpretations of NDC assumptions, and show that this results in estimated emissions for 2030 ranging from 47 to 63 GtCO2e yr-1. We show that this uncertainty has critical implications for the feasibility and cost to limit warming well below 2 °C and further to 1.5 °C. Countries are currently working towards clarifying the modalities of future NDCs. We identify salient avenues to reduce the overall uncertainty by about 10 percentage points through simple, technical clarifications regarding energy accounting rules. Remaining uncertainties depend to a large extent on politically valid choices about how NDCs are expressed, and therefore raise the importance of a thorough and robust process that keeps track of where emissions are heading over time

Global food efficiency of climate change mitigation in agriculture

Concerns exist regarding potential trade-offs between climate change mitigation in agriculture and food security. Against this background, the Global Biosphere Management Model (GLOBIOM) is applied to a range of scenarios of mitigation of emissions from agriculture to assess the implications of climate mitigation for agricultural production, prices and food availability. The “food efficiency of mitigation” (FEM) is introduced as a tool to make statements about how to attain desired levels of agricultural mitigation in the most efficient manner in terms of food security. It is applied to a range of policy scenarios which contrast a climate policy regime with full global collaboration to scenarios of fragmented climate policies that grant exemptions to selected developing country groups. Results indicate increasing marginal costs of abatement in terms of food calories and suggest that agricultural mitigation is most food efficient in a policy regime with global collaboration. Exemptions from this regime cause food efficiency losse

MESSAGEix workshop

The aim of the workshop is to help new users of the MESSAGEix modelling framework to get started with their modeling work. The main features of the “framework” are introduced, and the use cases of some features are shown. The user can learn how to build an energy model and how to represent some policy constraints in their energy scenarios. For information about the model, its structure, mathematical formulation and much more, please see the documentation at: https://docs.messageix.org. The different lectures contain the workshop slides, videos as well as tutorials for hands-on examples

Assessing the challenges of global long-term mitigation scenarios

The implications of global mitigation to achieve different long-term temperature goals (LTTGs) can be investigated in integrated assessment models (IAMs), which provide a large number of outputs including technology deployment levels, economic costs, carbon prices, annual rates of decarbonisation, degree of global net negative emissions required, as well as utilisation levels for fossil fuel plants. All of these factors can be considered in detail when judging the real-world feasibility of the mitigation scenarios produced by these models. This study presents a model inter-comparison of three widely used IAMs (TIAM, MESSAGE and WITCH) to analyse multiple mitigation scenarios exploring a range of LTTGs and a range of constraints, including delayed mitigation action, limited end-use electrification and delayed deployment of carbon capture technologies. The scenario outputs across the three models are examined and discussed and a matrix of the different factors concerning scenario feasibility is presented

The MESSAGEix Integrated Assessment Model and the ix modeling platform (ixmp)

The MESSAGE Integrated Assessment Model (IAM) developed by IIASA has been a central tool of energy-environment-economy systems analysis in the global scientific and policy arena. It played a major role in the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC); it provided marker scenarios of the Representative Concentration Pathways (RCPs) and the Shared Socio-Economic Pathways (SSPs); and it underpinned the analysis of the Global Energy Assessment (GEA). Alas, to provide relevant analysis for current and future challenges, numerical models of human and earth systems need to support higher spatial and temporal resolution, facilitate integration of data sources and methodologies across disciplines, and become open and transparent regarding the underlying data, methods, and the scientific workflow. In this manuscript, we present the building blocks of a new framework for an integrated assessment modeling platform; the \ecosystem" comprises: i) an open-source GAMS implementation of the MESSAGE energy++ system model integrated with the MACRO economic model; ii) a Java/database backend for version-controlled data management, iii) interfaces for the scientific programming languages Python & R for efficient input data and results processing workflows; and iv) a web-browser-based user interface for model/scenario management and intuitive \drag-and-drop" visualization of results. The framework aims to facilitate the highest level of openness for scientific analysis, bridging the need for transparency with efficient data processing and powerful numerical solvers. The platform is geared towards easy integration of data sources and models across disciplines, spatial scales and temporal disaggregation levels. All tools apply best-practice in collaborative software development, and comprehensive documentation of all building blocks and scripts is generated directly from the GAMS equations and the Java/Python/R source code