the interplay of climate change, agriculture, land use in a policy pool
INTEGRATED ASSESSMENT MODELING
Integrated assessment modeling ---> a common tool for assessing strategies to cope with climate change
--> describe complex relations between environment, social, and economic factors that determines future climate change and the effectiveness of climate policy
History
Early IA models typically only included atmospheric CO2 concentration and temperature changes as environmental variables --> they attempted to adopt and improve traditional decision analytic frameworks
Gradually, more details was added to IA models
Later, emphasis was put on selected aspects of climate change, and resulted in efforts aimed at creating frameworks specifically tailored to the climate change problem
Over the last decade, some IA models have expanded their coverage by considering land-use and terrestrial carbon cycle representation, non-CO2 gases and air pollutants, and by looking into specific impacts of climate change
Definition
IAM is distinguished by its holistic approach in representing causes and effects of climate change
The modeling is integrated because it crosses the borders between academic disciplines and integrates knowledge from two or more domains into a framework
In general, IAMs are composed of modules that cover essential parts of anthroposphere, the biosphere, and climate system.
A typical cause-effect chain starts from economic activities, and then translates emissions into changes in climate and related impacts on ecosystem, human health and agriculture, for example, including some feedbacks between these elements
As IAMs aim at integrating different disciplines, they run at risk of becoming extremely complex
In order to make their construction and use trackable, many IAMs use relatively simple equations to capture relevant phenomena.
Classification
Three different branches of IAMs and paradigms have evolved. Each of them puts a different domain at the center.
Nordhaus built his DICE model around an economic growth model.
Edmond started the construction of the MiniCAM model from an energy system model
Rotmans designed the IMAGE model based on comparatively detailed description of the biophysical system.
Goodness(2003) and Vuuren(2011) distinguish IA models that have a stronger focus on economics and other IA model that are more focused on the physical processes in both the natural system and the economy. Examples of the former are models focusing on cost-benefit analysis and multisectoral CGE models that are combined with climate modules. The latter are represented by integrated structural models and biophysical impact models.
IAMs can also be classified into policy evaluation and policy optimization models
Policy evaluation models are simulation models that calculate the implication of a user-defined policy(emission scenarios) for all explicitly modeled variables of interest to the policy maker: temperature changes, ecosystem and agricultural yield change and sea-level rises.
Policy optimization models can run in a cost-benefit framework such as RICE/DICE family of models or in a cost-effectiveness framework such as the MERGE model. The former determines optimal values for both the cost of mitigation and impacts. Recent attempts successfully include adaptation in the assessment. In a cost-effectiveness framework the acceptable impact is specified as an environmental target(emission budget target, CO2-equivalent concentration and temperature target) and the optimization is restricted to find the least-cost emission path to achieve that target.
Policy Tools
IAMs' main goal is to support policy making.
Policy issues addressed by IAM include determining global and regional cost and benefits of reducing future GHG emissions , identifying cost-effective emission reduction pathways to reach certain climate targets, as well as investigating the type of mitigation measures required for achieving a particular targets and describing the economic impacts of certain climate policies. IAMs are also applied to address potential conflicts that arise from climate policies that have contrary impacts across regions and across different domains
Components
Overview of the basic structure of an IAM composed of anthroposphere (or socioeconomic module) that can be considered as the driver of climate change, the climate module that reacts to this driver and impact module that is composed of a variety of natural system elements.
Within this decomposed structure, the land-use system plays a central role. It connects all other parts.
Moreover, the socioeconomic system is divided into 2 parts: an economy and energy systems sub-module. Both are linked by the demand of the economy for final energy for final energy. This demand has to be met by energy production within the energy system, which needs capital for investment in order to install capacities for energy production. In general, the energy system modules of IA models do not include capital markets, therefore the demand for investments have to be met via a link to economy module. Depending on choice of technology, energy production causes greenhouse gas emissions that enter the climate system. Induced climate change leads to climate impact that feedbacks into the socioeconomic system. Climate change also impacts the biospheric by changed precipitated patterns, increased temperature and CO2 fertilization.
With respect to implementation, both traditional approaches of model coupling have specific challenges. The hard-link approach results in the most consistent representation of the coupled system. However, transparency decreased and numerical efforts and maintenance demand increase. Consequently, the number and complexity of modules that can be coupled is limited. The soft-link approach can generally combine more modules. Nevertheless, the task of coordinating the communication and data flow between the modules is demanding. Feedbacks that for instance, represent the process of balancing demand and supply require an iterative process
AGRICULTURE AND LAND USE IN INTEGRATED ASSESSMENT MODELS
Dimensions of Agriculture and Land-use modeling
Agriculture and land use patterns are determined by a multitude of environment, economic and sociocultural conditions and their interactions. The competition of different types of land-use is a crucial issue --> between agriculture and forestry GHG mitigation
Currently, available IA models in three dimensions with regard to agriculture and land-use:
the level of detail in covering socioeconomic processes and conditions
the level of detail in biochemical process and conditions
the explicit coverage and detail of links and interactions between two spheres
The climate system interface
The climate system interface includes all climate-related natural conditions that favor or hinder the growth of agricultural crops,
Climate impacts on agriculture
Thus the magnitude of the positive e ect due to enhanced CO2concentration is still uncertain
Higher temperatures are to be expected in the future over the entire globe, but with significant regional and seasonal variation
Climate impacts on crop productivity will fundamentally depend on precipitation changes. Only a few IAM include a sufficiently elaborate hydrology component to capture the explicit links between water use in agriculture and other sectors as well as water availability
Climate variability, that is, extreme climate event may damage crop in specific development stage. However, this issues are currently not covered in the available IA modeling approaches.
GHG emissions related to agriculture and land-use change
while assessing climate change impact on the agricultural sector is one specific motivation to include agricultural sect is one specific motivation to include agriculture and land-use module in IA models, accounting for land-use-related emissions is another.
the contribution of agriculture to CO2 emission is negligible. CH4 is produced by anaerobic decomposition of organic matter mainly associated with enteric fermentation of ruminants, rice cultivation and manure storage.
N2O emission from agriculture are basically related to nitrogen fertilizers and manure applied to soils, but also manure storage
Some IA models projects emission of non-CO2 gases, while only few have detailed coverage of their impacts on the climate system as well as mitigation potential and options in the agricultural sector.
Land-use changes are a massive source of carbon emissions and contribute significantly to global warming due to the conversion of forests into agricultural land, but also as a result of expanding settlement.
The energy system interface
indirect influence emerging from different mitigation efforts in other sectors will play an important factors
Today almost all of the commercially available biofuels are produced from either starch or sugar-rich crops (for bioethanal) or oilseeds (for biodiesel)
combination of bioenergy and CCS, if bioenergy can be produced in a carbon-neutral way
the potential for bioenergy supply can be divided into three main categories: traditional bioenergy, agricultural and forest residues and bioenergy from dedicated energy crops
commercial bioenergy has an important role in almost all IAM scenario for future energy systems.
In energy system model today, total energy production costs are composed of technology-specific investment and maintenance costs as well as fuel cost
all of these impacts can only be studied in an integrated framework with specific implementation of models. Yet only a few models provide this detail
The socioeconomy interface
Food linkage
the main driver of agricultural production is food demand. The overall food demand depends on the number of population and on per capital income, and is therefore a variable of economic module. Basic needs in term of calorie requirement per capita can be used to derive minimum overall food demand.
while the details of this relationship are hardly modeled in any of the land-use modules in existing models, it is a quite important relationship
Investment linkage
Typically, land-use models are subject to land constraints but not to capital constraint. However, most of the yield increase in the past was not due to land expansion, but due to technical progress in several parts of the agricultural production system.
Land-use models often apply recursive dynamics with myopic agents, while economic growth models represent intertemporal dynamics with agents that have perfect foresight
Trade linkage
In the real world, countries that specialize in agricultural production accumulate revenues from exporting these products that allow them import manufacturing goods without running a current account deficit
A first step in the direction of integrated trade balance accounting is given by an approach that feeds agricultural trade volumes into each region's budget constraint.
This implies that each dollar of export surplus relaxes the budget constraint and qualifies for an import of another good with the value
IMPLEMENTATION OF LAND-USE IN INTEGRATED ASSESSMENT MODELS
IMAGE
The Integrated Model to Assess the Global Environment(IMAGE) links agricultural demands and supply for 24 world regions with a range of environmental parameters on a spatial grid with a resolution of 0.5*0.5 degrees
GCAM
The Global Assessment Model is a long-term, integrated assessment model. It combines a model of the global economy, energy systems and agriculture and land-use with representation of terrestrial and ocean carbon cycles.
IGSM
The Integrated System Model (IGSM) couples sub-models of the natural earth system to a model of human component