Integrated Assessment Modeling Framework Research Articles

Coupling an integrated assessment model with an input–output database

MESSAGE is an Integrated Assessment Model (IAM) useful for developing anthropogenic climate change scenarios and the evaluation of long-term energy policies. MESSAGE is constrained by its internal scenario generator, which project energy commodity demand inputs based only on population and GDP growth assumptions; the lack of sectoral and supply-chain details prevents modeling impacts from develpoments in non-energy sectors. Here we link MESSAGEix-Australia, a national-level MESSAGE IAM variant, to an input-output scenario builder to generate future energy commodity demands. The coupled IO_IAM framework then captures indirect energy implications of various socio-economic scenarios. Two scenarios were used to demonstrate this capability: first on the policy-based decarbonisation pathways for Australia, and second on the adoption of self-healing roads. This study showcases that a link between IO and IAM methods provides an opportunity for bringing together the strengths of the two approaches for assessing a wide range of sustainability questions.

The impacts of decarbonization pathways on Sustainable Development Goals in the European Union

Climate action to achieve the Paris Agreement should respect the United Nations Sustainable Development Goals. Here, we use an integrated assessment modelling framework comprising nine climate policy models and quantify the impacts of decarbonisation pathways on Sustainable Development Goals in the European Union at regional and national levels. We show that scenario-consistent assumptions of future socio-economic trends and current climate policies would improve energy- and carbon-related aspects of sustainability and reduce inequalities. Ambitious net-zero emissions pathways would further improve health and agricultural productivity. Furthermore, countries currently lagging in achieving sustainable development goals would see the greatest benefits from ambitious climate action. Negative socio-economic impacts from climate action on poverty, hunger, and economic growth will require specific corrective policies. While our analysis does not quantify the negative effects of less ambitious climate policy, it demonstrates where co-benefits and trade-offs of greenhouse gas mitigation and sustainable development agenda exist and can guide policy formulation.

Energy planning in Sub-Saharan African countries needs to explicitly consider productive uses of electricity

Studies show the role of various electrification technologies in providing electricity access to households in Sub-Saharan Africa, with a focus on electricity demand for end-use services such as lighting, cooking, heating, cooling and other appliance use. The demand for productive use of electricity, which is important to enhance income generation opportunities and labour productivity, is usually not considered. Using the IMAGE-TIMER integrated assessment model framework, we present a methodology to project the impact of productive activities on the electricity system of the region. We show that growing productive activities increase household electricity demand by half, which has important consequences for determining the cost-optimal electrification technologies. We argue that planning of electricity systems should accommodate this increase in electricity demand for productive uses. In addition, while productive uses of electricity have a positive impact on the financial viability of electrification systems, they also increase the electricity sector investment requirements considerably.

Net GHG emissions and air quality outcomes from different residential building electrification pathways within a California disadvantaged community

• Electrification can reduce net GHG emissions and public health impacts from PM-2.5 μ exposures. • Electrification of different gas appliances produces different load profile shapes. • Load profile shapes determine grid fossil generator unit responses and overall net impacts. • Local air quality benefits are principally determined by the volume of avoided gas use. • Ambient air quality impacts are principally determined by the timing of load profile changes. Electrification of gas appliances in residential buildings will be necessary to rapidly decarbonize the energy system. In California however, recent rates of adoption of electric appliances, especially within disadvantaged and vulnerable communities (DVCs), have been insufficient to meet the state's ambitious GHG emissions abatement targets. In this study we use an integrated assessment modeling framework to quantify the holistic benefits of different electrification pathways within a representative study area DVC. Results indicate that aggressive electrification retrofits can deliver significant net reductions in GHG emissions, even when future grid emissions from increased electric loads are factored in. We also find that these measures can also create significant net public health benefits, in terms of overall avoided impacts from particulate matter (PM-2.5 μ ) exposures. However, the realization of these net benefits requires tradeoffs between local improvements in air quality in the areas where electrification occurs, for smaller, but still significant, reductions in air quality, in areas where fossil fueled electricity generators remain active. We conclude with a discussion of some of the persistent barriers to electrification within DVCs and the import role of electrification within broader efforts to combat climate change and improve equity within the energy system.

Study of climate change impact on hydro-climatic extremes in the Hanjiang River basin, China, using CORDEX-EAS data

An integrated assessment modelling framework is introduced to comprehensively evaluate the climate change impact on hydro-climatic extremes over the Hanjiang River basin, China. The framework consists of climate model scenarios, bias correction method, hydrological model, and extreme climate and streamflow indices. The outputs from five CORDEX-EAS regional climate models (RCMs) under RCP 2.6 and 8.5 were firstly bias-corrected for two future windows, i.e. near future (2021-2050) and far future (2051-2080), and then used to drive a hydrological model to estimate the changes of extreme climate and streamflow, which were described by 19 standard hydro-climatic indices. The hydrological model was calibrated using a new software developed based on generalized likelihood uncertainty estimation (GLUE) algorithm under parallel computing environment. From the ensemble median of RCMs, it was found that the study basin is expected to be slightly wetter and significantly hotter in the future, with more intense and frequent precipitation and higher temperature extremes. Particularly, the extreme annual maximum 1-day streamflow index would have an overall increase across the basin, with the most significant increase in the south-western part of the basin. The extreme annual minimum 7-day streamflow index is projected to have a significant increase in the northern, south-western and south-eastern parts of the basin in the near future, while it would show a basin-wide decrease in the far future under RCP 8.5. Our findings helped gain an in-depth insight into the responses of hydro-climatic extremes to climate changes for a large-scale watershed and offer valuable guidance to decision makers who are responsible in designing adaptation strategies to mitigate the risks from extreme water-related disasters in the future.

MUSE: An open-source agent-based integrated assessment modelling framework

Integrated assessment models (IAMs) are a cornerstone of an effective approach to climate change mitigation. Despite the variety of methodologies for characterising the energy system, land use change, economics, and climate response, the modelling community has an open and urgent request for tools capable of more realistic interpretation of the energy transition, capturing human behaviour, and embodying the principles of transparency, reproducibility, and flexibility of use.This paper presents an open-source modelling framework designed to fill that gap. Named MUSE (ModUlar energy systems Simulation Environment), this new agent-based model supports flexible characterisation of agent decision-making, including individual goals, bounded-rationality, imperfect foresight, and limited knowledge during the decision process. MUSE integrates this agent-based approach in a partial-equilibrium framework and enables a technology-rich description of the energy systems with an unprecedented degree of flexibility for including technological, temporal, and geographical granularity. The structure of MUSE creates the ability to produce climate change mitigation assessments that are more grounded, and more tangible model outputs for conceiving effective approaches to mitigation. MUSE is available open source under a GNU General Public License v3.0 on GitHub at this link https://github.com/SGIModel/MUSE_OS.

The Development of a Framework for the Integrated Assessment of SDG Trade-Offs in the Sundarban Biosphere Reserve

The United Nations Sustainable Development Goals (SDGs) and their corresponding targets are significantly interconnected, with many interactions, synergies, and trade-offs between individual goals across multiple temporal and spatial scales. This paper proposes a framework for the Integrated Assessment Modelling (IAM) of a complex deltaic socio-ecological system in order to analyze such SDG interactions. We focused on the Sundarban Biosphere Reserve (SBR), India, within the Ganges-Brahmaputra-Meghna Delta. It is densely populated with 4.4 million people (2011), high levels of poverty, and a strong dependence on rural livelihoods. It is adjacent to the growing megacity of Kolkata. The area also includes the Indian portion of the world’s largest mangrove forest––the Sundarbans––hosting the iconic Bengal Tiger. Like all deltaic systems, this area is subject to multiple drivers of environmental change operating across scales. The IAM framework is designed to investigate socio-environmental change under a range of explorative and/or normative scenarios and explore associated policy impacts, considering a broad range of subthematic SDG indicators. The following elements were explicitly considered: (1) agriculture; (2) aquaculture; (3) mangroves; (4) fisheries; and (5) multidimensional poverty. Key questions that can be addressed include the implications of changing monsoon patterns, trade-offs between agriculture and aquaculture, or the future of the Sundarbans’ mangroves under sea-level rise and different management strategies. The novel, high-resolution analysis of SDG interactions allowed by the IAM will provide stakeholders and policy makers the opportunity to prioritize and explore the SDG targets that are most relevant to the SBR and provide a foundation for further integrated analysis.

Air quality and health co-benefits of China's national emission trading system

Quantification of the air quality and health co-benefits of climate policies can provide explicit near-term localized assessment of the benefits of efforts to mitigate climate change. In the study, the air quality and PM2.5 associated health co-benefits of China's national Emission Trading System to achieve the Nationally Determined Contribution is analyzed. The interdisciplinary integrated assessment model framework, named the Regional Emissions Air quality Climate Health Model, is applied. The results showed that substantial air quality improvement and health benefit will be achieved under the national Emission Trading System. But the cost and benefits varies according to the CO2 emission cap set. To peak CO2 emissions by 2025 will bring about more obvious improvement in air quality (ranging from 3% to 12% PM2.5 concentration reduction at provincial level compared with that to peak CO2 emission by 2030), more morbidities avoided from acute exposure and more mortalities avoided from acute exposure and chronic exposure. While the net health benefit to achieve peaking by 2025 is US$ 100 billion less than that to achieve peaking by 2030 due to greater GDP loss in 2030. The net benefit is subjected to the valuation of the health benefits. If a higher Value of a Statistical Life, US$ 1.92 million, is chosen, the net benefits to achieve peak CO2 emissions by 2025 can be equal to that to achieve peak CO2 emissions by 2030.

MEDEAS: a new modeling framework integrating global biophysical and socioeconomic constraints

Description of the open-source MEDEAS integrated assessment modeling framework, which focuses on the biophysical and economic dimensions, restrictions and interactions arising during energy transitions.

Afforestation for climate change mitigation: Potentials, risks and trade-offs.

Afforestation is considered a cost-effective and readily available climate change mitigation option. In recent studies afforestation is presented as a major solution to limit climate change. However, estimates of afforestation potential vary widely. Moreover, the risks in global mitigation policy and the negative trade-offs with food security are often not considered. Here we present a new approach to assess the economic potential of afforestation with the IMAGE 3.0 integrated assessment model framework. In addition, we discuss the role of afforestation in mitigation pathways and the effects of afforestation on the food system under increasingly ambitious climate targets. We show that afforestation has a mitigation potential of 4.9GtCO2 /year at 200 US$/tCO2 in 2050 leading to large-scale application in an SSP2 scenario aiming for 2°C (410GtCO2 cumulative up to 2100). Afforestation reduces the overall costs of mitigation policy. However, it may lead to lower mitigation ambition and lock-in situations in other sectors. Moreover, it bears risks to implementation and permanence as the negative emissions are increasingly located in regions with high investment risks and weak governance, for example in Sub-Saharan Africa. Afforestation also requires large amounts of land (up to 1,100 Mha) leading to large reductions in agricultural land. The increased competition for land could lead to higher food prices and an increased population at risk of hunger. Our results confirm that afforestation has substantial potential for mitigation. At the same time, we highlight that major risks and trade-offs are involved. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade-offs in order to achieve mitigation sustainably.

Biodiversity can benefit from climate stabilization despite adverse side effects of land-based mitigation

Limiting the magnitude of climate change via stringent greenhouse gas (GHG) mitigation is necessary to prevent further biodiversity loss. However, some strategies to mitigate GHG emission involve greater land-based mitigation efforts, which may cause biodiversity loss from land-use changes. Here we estimate how climate and land-based mitigation efforts interact with global biodiversity by using an integrated assessment model framework to project potential habitat for five major taxonomic groups. We find that stringent GHG mitigation can generally bring a net benefit to global biodiversity even if land-based mitigation is adopted. This trend is strengthened in the latter half of this century. In contrast, some regions projected to experience much growth in land-based mitigation efforts (i.e., Europe and Oceania) are expected to suffer biodiversity loss. Our results support the enactment of stringent GHG mitigation policies in terms of biodiversity. To conserve local biodiversity, however, these policies must be carefully designed in conjunction with land-use regulations and societal transformation in order to minimize the conversion of natural habitats.

Global advanced bioenergy potential under environmental protection policies and societal transformation measures

AbstractBioenergy plays an important role in low greenhouse gas stabilization scenarios. Among various possible sources of bioenergy, dedicated bio‐crops could contribute to most of the potential. However, large scale bio‐crop deployment raises sustainability concerns. Policies to alleviate the pressure of bio‐crops on the terrestrial environment can affect bioenergy potential and production costs. Here, we estimated the maximum bioenergy potential under environmental protection policies (biodiversity and soil protection) and societal transformation measures from demand and supply side (demand‐side policy includes sustainable diet; supply‐side policy includes advanced technology and trade openness for food) by using an integrated assessment modelling framework, which consists of a general equilibrium model (Asian‐Pacific Integrated Model/Computable General Equilibrium) and a spatial land use allocation model (Asian‐Pacific Integrated Model/Platform for Land‐Use and Environmental Model). We found that the global advanced bioenergy potential under no policy was 245 EJ/year and that 192 EJ/year could be produced under US$5/GJ. These figures were 149 EJ/year and 110 EJ/year, respectively, under a full environmental policy. Biodiversity protection has a greater impact than soil protection due to its larger coverage and stronger implementation. Societal transformation measures effectively increase them to 186 EJ/year and 143 EJ/year, respectively, even under full environmental policies. These results imply that the large‐scale bioenergy deployment possibly needed for the climate target to limit the global mean temperature increase well below 2°C compared to the preindustrial level might face a trade‐off with environmental protection targets and that possible mitigation pathways in harmony with other environmental issues need to be explored.

Gridded emissions and land-use data for 2005\u20132100 under diverse socioeconomic and climate mitigation scenarios

Information on global future gridded emissions and land-use scenarios is critical for many climate and global environmental modelling studies. Here, we generated such data using an integrated assessment model (IAM) and have made the data publicly available. Although the Coupled Model Inter-comparison Project Phase 6 (CMIP6) offers similar data, our dataset has two advantages. First, the data cover a full range and combinations of socioeconomic and climate mitigation levels, which are considered as a range of plausible futures in the climate research community. Second, we provide this dataset based on a single integrated assessment modelling framework that enables a focus on purely socioeconomic factors or climate mitigation levels, which is unavailable in CMIP6 data, since it incorporates the outcomes of each IAM scenario. We compared our data with existing gridded data to identify the characteristics of the dataset and found both agreements and disagreements. This dataset can contribute to global environmental modelling efforts, in particular for researchers who want to investigate socioeconomic and climate factors independently.

A low energy demand scenario for meeting the 1.5 °C target and sustainable development goals without negative emission technologies

Scenarios that limit global warming to 1.5 °C describe major transformations in energy supply and ever-rising energy demand. Here, we provide a contrasting perspective by developing a narrative of future change based on observable trends that results in low energy demand. We describe and quantify changes in activity levels and energy intensity in the global North and global South for all major energy services. We project that global final energy demand by 2050 reduces to 245 EJ, around 40% lower than today, despite rises in population, income and activity. Using an integrated assessment modelling framework, we show how changes in the quantity and type of energy services drive structural change in intermediate and upstream supply sectors (energy and land use). Down-sizing the global energy system dramatically improves the feasibility of a low-carbon supply-side transformation. Our scenario meets the 1.5 °C climate target as well as many sustainable development goals, without relying on negative emission technologies. Achieving sustainable development goals while meeting the 1.5 °C climate target requires radical changes to how we use energy. A scenario of low energy demand shows how this can be done by down-sizing the global energy system to enable feasible deployment rates of renewable energy resources.

Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation

Abstract Projected increases in population, income and consumption rates are expected to lead to rising pressure on the land system. Ambitions to limit global warming to 2 °C or even 1.5 °C could also lead to additional pressures from land-based mitigation measures such as bioenergy production and afforestation. To investigate these dynamics, this paper describes five elaborations of the Shared Socio-economic Pathways (SSP) using the IMAGE 3.0 integrated assessment model framework to produce regional and gridded scenarios up to the year 2100. Additionally, land-based climate change mitigation is modelled aiming for long-term mitigation targets including 1.5 °C. Results show diverging global trends in agricultural land in the baseline scenarios ranging from an expansion of nearly 826 Mha in SSP3 to a decrease of more than 305 Mha in SSP1 for the period 2010–2050. Key drivers are population growth, changes in food consumption, and agricultural efficiency. The largest changes take place in Sub-Saharan Africa in SSP3 and SSP4, predominantly due to high population growth. With low increases in agricultural efficiency this leads to expansion of agricultural land and reduced food security. Land use also plays a crucial role in ambitious mitigation scenarios. First, agricultural emissions could form a substantial component of emissions that cannot be fully mitigated. Second, bioenergy and reforestation are crucial to create net negative emissions reducing emissions in SSP2 in 2050 by 8.7 Gt CO2/yr and 1.9 Gt CO2/yr, respectively (1.5 °C scenario compared to baseline). This is achieved by expansion of bioenergy area (516 Mha in 2050) and reforestation. Expansion of agriculture for food production is reduced due to REDD policy (290 Mha in 2050) affecting food security especially in Sub-Saharan Africa indicating an important trade-off of land-based mitigation. This set of SSP land-use scenarios provides a comprehensive quantification of interacting trends in the land system, both socio-economic and biophysical. By providing high resolution data, the scenario output can improve interactions between climate research and impact studies.

Impacts of climate mitigation strategies in the energy sector on global land use and carbon balance

Abstract. Reducing greenhouse gas emissions to limit damage to the global economy climate-change-induced and secure the livelihoods of future generations requires ambitious mitigation strategies. The introduction of a global carbon tax on fossil fuels is tested here as a mitigation strategy to reduce atmospheric CO2 concentrations and radiative forcing. Taxation of fossil fuels potentially leads to changed composition of energy sources, including a larger relative contribution from bioenergy. Further, the introduction of a mitigation strategy reduces climate-change-induced damage to the global economy, and thus can indirectly affect consumption patterns and investments in agricultural technologies and yield enhancement. Here we assess the implications of changes in bioenergy demand as well as the indirectly caused changes in consumption and crop yields for global and national cropland area and terrestrial biosphere carbon balance. We apply a novel integrated assessment modelling framework, combining three previously published models (a climate–economy model, a socio-economic land use model and an ecosystem model). We develop reference and mitigation scenarios based on the narratives and key elements of the shared socio-economic pathways (SSPs). Taking emissions from the land use sector into account, we find that the introduction of a global carbon tax on the fossil fuel sector is an effective mitigation strategy only for scenarios with low population development and strong sustainability criteria (SSP1 Taking the green road). For scenarios with high population growth, low technological development and bioenergy production the high demand for cropland causes the terrestrial biosphere to switch from being a carbon sink to a source by the end of the 21st century.

Long-term carbon dioxide and hydrofluorocarbon emissions from commercial space cooling and refrigeration in India: a detailed analysis within an integrated assessment modelling framework

Quantification of greenhouse gas emissions is a critical research gap for space cooling and refrigeration applications in Indian commercial buildings. This is especially relevant as these services are expected to grow rapidly in future driven by economic growth and urbanisation. This paper focuses on these two applications which are highly energy and emission intensive, and quantifies their carbon dioxide (CO2) and hydrofluorocarbon (HFC) emissions through soft-linking a top-down model with a bottom-up approach. An integrated assessment modelling framework Global Change Assessment Model (GCAM)-IIM is used for modelling energy-related emissions under a business-as-usual scenario. In addition to CO2 emissions occurring from electricity use, cooling and refrigeration in commercial buildings emit another set of highly potent greenhouse gases, emanating from application of HFCs as coolant. HFCs substitute their ozone-depleting precursors in these applications. Countries across the world have agreed to phase down HFCs under the Montreal Protocol. Before we can analyse cost-effective options to bring down these emissions, it is important to quantify and assess the amount of emissions that could be avoided in the future. Our research sets up a baseline for carbon dioxide and HFC emissions from India for the commercial air-conditioning and refrigeration sectors and finds the potential HFC emission mitigation due to the Kigali Amendment. A detailed bottom-up modelling of these emissions is undertaken and it is found that, if unabated, the HFC emissions from commercial sector will surge from mere 1.8 million tonne (Mt) CO2e in 2015 to 211 Mt CO2e in 2050, whereas energy-related CO2 emissions from commercial air-conditioning and refrigeration will rise from 37 to 297 Mt CO2e in the same period. We also highlight the role of management practices and regulation for curbing HFC emissions which is especially relevant for the commercial building sector.

Fossil-fueled development (SSP5): An energy and resource intensive scenario for the 21st century

This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development.

A framework for integrated assessment of food production economics in South Asia under climate change

Agriculture is a sector vulnerable to climate change. The potential decline of crop yields from this vulnerability has important policy implications for food security in South Asia. In this study an integrated assessment modelling framework is proposed to link a global economic model with global climate models via an econometric model of crop productivity. It is then used to examine the impact of climate change on food security in individual South Asian countries by exploring the interaction between climate-induced productivity change and changes in food production and food prices. The results of our simulations suggest that unfavourable climate change can reduce food production significantly from the historical trend and create upward pressure on food prices. This, in turn, will have serious adverse impacts on food security in the South Asian region.

Growth and competition in renewable energy industries: Insights from an integrated assessment model with strategic firms

This article describes the development, implementation, and application of an integrated assessment modeling framework featuring renewable technology markets with producers engaged in Cournot competition. Scenario results reveal how climate policy and inter-firm learning spillovers interact with market structure to affect wind and solar PV prices, adoption, producer profits, and carbon emissions. Competitive markets yield consistently lower markups than concentrated markets, leading to significantly more adoption and lower emissions. Widespread solar PV adoption is a key component of the largest emissions reductions, but this requires substantial price reductions that only occur if the solar PV market is competitive and learning spills over across producers. Whether a leading firm has a profit incentive to facilitate or obstruct learning spillovers depends on the availability of cost-competitive substitute technologies. If such a substitute exists, the firm prefers strong spillovers that help its industry compete against the substitute; if not, the firm prefers weak spillovers that prevent competitors in its industry from seizing market share. The relationship between price and cumulative capacity is endogenous in the modeling framework. Regression analysis of scenario results yields price learning rates which are similar to unit production cost learning rates in competitive markets, but substantially lower – even negative – in concentrated markets.