AMP Toolbox

b) Integrated Model to Assess the Global Environment (IMAGE 2.4)
Step 1- Setting the scene, Step 3 - Making the policy robust and Step 5 - Evaluation and policy adjustments.
Activity 1.4- Scenario analysis (including risk assessment)

IMAGE is an Integrated Assessment Model (IAM) to simulate the environmental consequences of human activity worldwide. It has been designed to simulate the dynamics and interconnections between three major subsystems on earth (i.e. climate, biosphere and society), to assess sustainability issues regarding climate change, biodiversity and human well-being.

Integrated Assessment Models (IAM) are mathematical computer models based on explicit assumptions about how the modelled system behaves. The strength of an IAM is its ability to calculate the consequences of different assumptions and to inter-relate may factors simultaneously, but an IAM is constrained by the quality and character of the assumptions and data that underlie the model.
Most climate change integrated assessment projects now underway are developing an integrated model. These models provide a very useful framework or methodology for organising and assessing information and for conducting research. They allow for consistency in the integration and assessment of information, and they are useful in illustrating where research and knowledge is lacking as well as having insights into the consequences of different policy options.
Integrated assessment models generally include both physical and social science models that consider demographic, political, and economic variables that affect greenhouse gas emission scenarios in addition to the physical climate system. Climate change IAMs are tools that bring together very different types of information (e.g., knowledge about climate, economics, ecology) in a coherent framework that is usable by researchers and decision makers.
IAMs cannot provide "the answer" about how to respond to the climate change problem. IAMs, however, can provide a framework for understanding the climate change problem and for informing judgements about the relative value of different option for dealing with climate change. In this sense, they can be used in a predictive mode, quantifying scenarios. IMAGE has been used this way for the Millennium Ecosystem Assessment (Alcamo et al., 2005) and for the PERSEUS project.
In predictive mode, formal sensitivity analysis must be developed as part of the global modelling exercise to estimate the uncertainty of calculations.

Different IAMs exist, however each one approaches the climate change issue in a different manner. For example, some models focus more on economic issues (e.g., DICE) while others are predominately physical models (e.g., MAGICC), and some models have a global focus (e.g., IMAGE 2.4 or MiniCAM) while others are regional (e.g. AIM).

In the case of the IMAGE model, the assumptions of the model are based on the development of population and Gross Domestic Product (GDP) as provided by socio-economic scenarios (e.g. IPCC-SRES, Millennium Ecosystem Assessment, SSP and other scenarios). Regional energy consumption, energy efficiency improvement, fuel substitution, supply and trade of fossil fuels and renewable energy technologies are simulated with the specific energy model to calculate energy production, energy use, industrial production, emissions of greenhouse gases, ozone precursors and sulphur. Ecosystem, crop and land-use models are used to compute land use on the basis of regional consumption, technological developments, production and trading of food, animal feed, grass and timber, and local climatic and terrain properties. The use of detergent is modelled on the base of GDP and assumptions on specific policies and the resulting impact on water quality are assessed. Figure 4 shows the framework of the IMAGE model.

Figure 1: Schematic diagram of IMAGE 2.4 and model details.

Before choosing an IAM, the following issues should be considered:
 choose a model that most closely addresses the question
 choose a model that produces results at the spatial scale that is most appropriate for the task
 choose a model that is most appropriate for addressing the key sectors
 choose a model that is appropriate for the target audience
 choose a model that is well documented with explicit assumptions
 choose a model in which uncertainties are specified in model inputs and reflected in model outputs
 choose a model that has been exposed to careful peer review
 choose a model that is not so complex that it cannot be understood
 choose a model that has been developed by a team of experts with the background and expertise appropriate for addressing the question.

The current version of the Integrated Model to Assess the Global Environment (IMAGE 2.4), described in this chapter, represents the latest incarnation of a development that goes back as far as the late 1980s. Then a team at the National Institute for Public Health and the Environment (RIVM) in Bilthoven, the Netherlands, embarked on developing a global model to explore relevant aspects of climate change, emerging in those years as an important case for internationally concerted policy deliberations. The first version (1.0), formerly known as the Integrated Model to Assess the Greenhouse Effect (IMAGE), was a global, single-region model describing global trends in driving forces and the ensuing consequences for climatic change and impacts on key sectors, through a coupled set of modules representing the main processes involved. At the time, IMAGE 1.0 was among the first pioneering examples of Integrated Assessment Models addressing climate change.
Since then, IMAGE has evolved through a series of new versions, each introducing major revisions, enhancements and extensions up to the current version (IMAGE 2.4). This version marks an important milestone on the development path towards a next generation model, referred to as IMAGE 3, aimed at capturing – to a greater extent – the different aspects and domains of sustainability, with emphasis on the ecological domain but also related to the economic and social domains.
Specific features of the IMAGE model include comprehensive coverage of direct and indirect pressures on human and natural systems, closely related to human activities in industry, housing, transport, agriculture and forestry. The socio-economic activities and drivers of change are elaborated at 24 region levels, while the climate, land-cover and land-use change-related processes are represented in a geographically explicit manner on the 0.5 by 0.5 degree grid scale. It is this latter characteristic, relatively rare in integrated assessment models, that makes IMAGE particularly suited to exploring interactions between human and natural systems (Kram and Stehfest, 2011).

The scenario storylines produced by IMAGE can then be translated to assumptions regarding different management schemes such as nutrients management. For example, for the calculation of different nutrient policy scenarios (wastewater treatment based on Millennium Goals, fertilizer use efficiency, manure management, recycling of human excreta; aquaculture, use of P-based detergents), addressing development of agricultural demand, trade and production, and including the environmentally relevant aspects (livestock production, crop production).
In PERSEUS, for instance, the CEFREM model has been employed to compute river nutrient export to the coastal zone and provides a simulation of nutrient distribution in marine waters, based on the soil nutrient budgets and wastewater emissions provided by the IMAGE model. In the context of policies and strategies for marine areas, the use of IMAGE allows for the simulation of future discharge loads to be expected from different socio-economic and climate developments as well as from policy measures aiming at the reduction of nutrient discharges into rivers and seas.

Moderate - high.

High. Apart from the costs associated with the collation of data and expertise to use this method appropriately, is any license needed?

Moderate - high. This is a technical process that requires expertise using modeling techniques as well as knowledge of the interactions of the human activities with the biophysical environment.

Background requirements
Very high.

Low. It is a technical exercise where no stakeholder participation is required, once the scenarios have been chosen.

Time range
High. Time is required to gather the data necessary to complete the analysis. In addition, months are required to run a simulation and complete the process.

Source of information
 Alcamo J. et al, (2005), in Ecosystems and Human Well-being: Scenarios: Findings of the Scenarios Working Group, Millennium Ecosystem Assessment, edited by Steve R. Carpenter et al.
 Bouwman, A.F., Kram, T., Klein Goldewijk, K., (2006), Integrated modelling of global environmental change. An overview of IMAGE 2.4.
Netherlands Environmental Assessment Agency (MNP), Bilthoven, Netherlands.
Integrated Assessment Modeling 10 Things to Know.
IMAGE model site.
 Kram, T. and Stehfest, E., (2011), Integrated Modeling of Global Environmental Change. In: Land use, climate change and biodiversity modeling: perspectives and applications, Trisurat, Y., Shrestha, R.P. and Alkemade, R. (Eds.), (2011), pp.104-118.