GeoJournal 61: 381–393, 2004. Ó 2004 Kluwer Academic Publishers. Printed in the Netherlands.
381
The land-use projections and resulting emissions in the IPCC SRES scenarios as simulated by the IMAGE 2.2 model Bart Strengers1, Rik Leemans1,2, Bas Eickhout1, Bert de Vries1 & Lex Bouwman1 1
National Institute of Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands (Tel: +31-30-2743377; Fax: +31-30-2744435; E-mail:
[email protected]); 2Environmental Systems Analysis Group, Wageningen UR, Wageningen, The Netherlands
Key words: Land-use change, land-use emissions, SRES, IPCC, climate change, IMAGE model
Abstract The Intergovernmental Panel on Climate Change (IPCC) developed a new series of emission scenarios (SRES). Six global models were used to develop SRES but most focused primarily on energy and industry related emissions. Land-use emissions were only covered by three models, where IMAGE included the most detailed, spatially explicit description of global land-use and land-cover dynamics. To complement their calculations the other models used land-use emission from AIM and IMAGE, leading to inconsistent estimates. Representation of the land-use emissions in SRES is therefore poor. This paper presents details on the IMAGE 2.1 land-use results to complement the SRES report. The IMAGE SRES scenarios are based on the original IPCC SRES assumptions and narratives using the latest version of IMAGE (IMAGE 2.2). IMAGE provides comprehensive emission estimates because not only emissions are addressed but also the resulting atmospheric concentrations, c1imate change and impacts. Additionally, in SRES the scenario assumptions were only presented and quantified for 4 ‘‘macro-regions’’. The IMAGE 2.2 SRES implementation has been extended towards 17 regions. We focus on land-use aspects and show that land-related emissions not only depend on population projections but also on the temporal and spatial dynamics of different land-related sources and sinks of greenhouse gases. We also illustrate the importance of systemic feed backs and interactions in the c1imate system that influence land-use emissions, such as deforestation and forest regrowth, soil respiration and CO2-fertilisation. Introduction Over the last decades it has become likely that the observed increase in concentrations of greenhouse gases (GHGs) has increased global temperatures and altered climate patterns (Houghton et al., 2001). These changes are most likely to intensify in this century. The increase in concentrations is due to emissions of CO2, CH4, N2O and others. CO2 emissions are the result of the combustion of fossil fuels and cement production (approximately 80%) and land-use changes (mainly deforestation; approximately 20%). The emissions of CH4 and N2O are more strongly dominated by land-use activities. Land-use emissions stem from activities such as deforestation, biomass burning, fertiliser use, paddy rice cultivation and landfills. The Intergovernmental Panel on Climate Change (IPCC) recently developed a series of Standardised Reference Emissions Scenarios (SRES). The objective was to review existing emission scenarios and to revise the earlier IPCC IS92 emission scenarios dating from 1992 (Leggett et al., 1992). The SRES scenarios project future GHG emissions from all sectors, without considering specific climate policies and their impact on
emission reductions. As such the scenarios would provide a baseline or benchmark against which the effectiveness of specific policies could be assessed. The SRES scenarios were published (Nakicenovic et al., 2000) and partly used in the third assessment of IPCC (IPCC, 2001). The SRES team has developed innovative approaches to increase the utility of the emissions scenarios. The earlier IS92 scenarios (Leggett et al., 1992) were based upon a simple approach in which scenario assumptions were evaluated independently. The most likely trends and uncertainty ranges in population, wealth, technology, equity and energy use, established by experts judgements or literature surveys, were used to generate high, medium and low emissions pathways. This resulted in continuously increasing emissions. The middle scenario (labelled IS92a) is the still the most widely used in climate-change impact assessments. The SRES-approach is centred around four narratives or story-lines, each describing in qualitative terms how the economy, demography, technology, etc. evolves in a consistent way. Each narrative defines characteristic trends in the input assumptions of the various models.
382 This approach recognises explicitly that different assumptions are correlated. The narratives provide a wealth of information within each scenario although actual future developments remain uncertain. The narratives describe plausible future worlds but not credible real worlds. The actual developments will always be combinations of the selected dimensions. One of the larger advantages of the approach is it provides a clear context in which other aspects, such as local and regional aspects or mitigation or adaptation potential, can be more easily assessed. For example, in a global economy new technologies spread rapidly, which should also reduce gaps in agricultural productivity between countries. Fourteen modelling groups have implemented some or most of the narratives into their models (Nakicenovic et al., 2000). The SRES methodology resulted in a set of six marker scenarios, each with an additional range of emissions based on the simulations by the other models. In total 40 different realisations of these narratives have been used in the SRES report. IPCC has estimated the ranges in increases in concentrations and global mean temperature. Although in some scenarios, emissions peak after several decades, all scenarios depict that concentrations continue to increase, which lead to global mean temperature increases ranging from 1.5 to 5.8 °C in 2100. In a world without climate-change policies, climate is expected to change drastically. The models used by the SRES team strongly focused on energy and industry related emissions. These sectors control large parts of the total emissions but not all. Unfortunately, land-use emissions were neglected by most of the models. Only few models (ASF: Lashof and Tirpak, 1990; IMAGE 2.1: Alcamo et al., 1998; and AIM: Kainuma et al., 2002) explicitly modelled land-use change and related emissions. ASF only models the CO2 related land-use emissions, while IMAGE and AIM also include the other gases. The latter two models include spatially explicit land-use models that simulate crop productivity patterns. The land-use related emissions were taken from these models by the energy modelling teams to compliment their calculations. This approach will surely have led to some unreliable estimates but its consequences were not evaluated. Although, the SRES effort was a landmark in scenario development, the treatment of land-use emissions was poor. The resolution of the land-use emissions was also too coarse to provide adequate input to other studies. Here we present an implementation of the SRES scenarios in the IMAGE 2.2 model (IMAGE team, 2001a). IMAGE 2.2 is an improved version of the model that was used as part of the SRES effort. It models landuse change in 17 regions (for the socio-economic factors, such as food demand) and on a half-by-half degree grid (environmental factors, such as climate, land cover and soil properties) instead of the 13 regions version used for the original SRES exercise. The IMAGE team has now implemented all SRES narratives and also provided
some insights on uncertainties by including scenario runs with high, medium and low climate sensitivities (IMAGE team, 2001a) and using different GCM-based climate-change patterns to address impacts and feedbacks (IMAGE team, 2001b). These IMAGE 2.2 SRES scenarios do not only quantify the different sources of GHG emissions and SO2, but also calculates the resulting concentrations, climate change and impacts and adjusts for interactions between individual components. Some of these interactions are important in defining the land-use emissions. Inclusion of climate and CO2-related interactions in IMAGE additionally enhances the consistency and realism of the scenarios. In this paper, we focus on the land-use aspects in the SRES scenarios. First we will summarise some of the relevant characteristics of the IMAGE 2.2 model and the SRES narratives. The aim is reliably estimate landuse emissions by explicitly modelling the temporal and spatial dynamics of different sources and sinks of GHGs. The resulting scenario data could provide reliable input data for other studies. Our updated land-use emissions are summarised in Table 4. This Table is formatted along the lines of the original SRES data sets to allow for a broad use. In the latter part of the paper we’ll present some of these results to give an impression of their richness, their dynamics and the differences between the scenarios. We’ll show that the land-use projections do not only depend on population projections but that many other aspects define the outcome. We will also illustrate the importance of some of the systemic feedbacks and interactions in the climate systems that influence land-use emissions.
Introduction to IMAGE 2.2 IMAGE 2.2 (Integrated Model to Assess the Global Environment) is an integrated assessment model that calculates the environmental consequences of human activities. The objective of the IMAGE 2.2 model is to explore the long-term dynamics of global environmental change. This requires a dynamic representation of the evolution of the world system. Future greenhouse gas emissions, for example, are the result of complex interacting demographic, technological, economical, social, cultural and political forces. Scenarios are alternative representations of how the future might unfold. IMAGE 2.2 is especially developed to implement and analyse the outcome of these scenarios in a comprehensive way. The IMAGE-2 model is documented in Alcamo et al. (1998) and by the IMAGE team (2001a). The model consists of several modules (Figure 1). Interactions and feedbacks are modelled explicitly. In the IMAGE 2.2 framework the general equilibrium economy model, WorldScan (CPB, 1999), and the population model, PHOENIX (Hilderink, 1999), supply the basic information on economic and demographic developments for 17 world regions. Regional energy consumption, energy efficiency improvements, fuel substitution,
383
Figure 1. The structure of the IMAGE 2.2 model.
supply and trade of fossil fuels and renewable energy technologies determine energy production, energy use industrial production and emissions of GHGs, ozone precursors and SO2. Ecosystem, crop and land-use models are used to compute land use on the basis of regional consumption, production and trading of food, animal feed, fodder, grass and timber, and local climatic and terrain properties. GHG emissions from land-use change, natural ecosystems and agriculture, and the exchange of CO2 between terrestrial ecosystems and the atmosphere are determined. The atmosphere and oceans models calculate changes in atmospheric composition by employing the emissions and by taking oceanic CO2 uptake and atmospheric chemistry into consideration. Subsequently, changes in climatic properties are computed by resolving oceanic heat transport and the changes in radiative forcing by GHGs and aerosols (i.e. SO2) The impact models involve specific models for sealevel rise and land degradation risk and make use of specific features of the ecosystem and crop models to depict impacts on vegetation. Historical data for CO2 concentrations over the period 1765–1995 are used to initialise the carbon cycle and climate system (temperature, CO2 concentrations and net ecosystem productivity). Data for 1970–1995 are used to calibrate the energy, climate and land-use variables of the model. IMAGE 2.2 projections cover the 1995–2100 period. These simulations are made on the basis of scenario assumptions on, for example, demography, food and energy consumption and technology and trade. Although IMAGE 2.2 is global in application,
it performs many of its calculations either on a highresolution terrestrial 0.5 by 0.5-degree grid (crop yields and crop distribution, land cover, land-use emissions and carbon cycle) or for 17 world regions (population, energy, trade, industry and their emissions). This approach allows linking the different socio-economic and environmental dimensions and scale levels.
A short description of the SRES narratives Scenarios are alternative representations of how the future might unfold. They form an appropriate tool in analysing how driving forces may influence future emissions and in assessing the associated uncertainties. This was the main purpose of the SRES scenarios (Nakicenovic et al., 2000). These scenarios are based on a thorough review of the literature, the development of ‘narratives’ or storylines and the quantification of these narratives using different integrated models. We will summarise some of the main elements of the SRES scenarios here. For further details we refer the reader to the original SRES report (Nakicenovic et al., 2000). The SRES narratives were constructed along two approximate dimensions, i.e. the degree of globalisation versus regionalisation, and the degree of orientation on material values versus social and ecological values (see Figure 2). The narratives describe developments in many different social, economic, technological, environmental
384 regional differences in per capita income. The A1 scenario family develops into three groups that describe alternative directions of technological change in the energy system. These groups makes some additional assumptions explicit and enhance the diversity of scenarios. The three A1 groups are distinguished by their technological emphasis of the different energy carriers: fossil intensive (A1F), which continues to have a large share of fossil fuels; non-fossil energy sources (A1T) with a conversions towards less carbon intensive fuels; balanced across all sources (A1B) provides a mixed of fossil and non-fossil fuels. Figure 2. The dimensions of the four SRES scenarios.
The A2 narrative and policy dimensions. The narratives do not have a particular order, but they are listed alphabetically and numerically. The scenarios covered a wide range of futures, but not all-possible futures. Specifically: The two dimensions do not pretend to be complete; such important aspects as governance and technology are either absent or implicit. Neither should any of these future worlds be interpreted as a blueprint of some probability or desirability. Some regions of the world will evolve in the direction of globalisation, other regions in the direction of regionalisation while influencing each other in these evolutions. The scenarios only indicate possible futures if certain regions, values and mechanisms become more dominant than others. Neither should the four scenario clusters be seen as a stable endpoint. They interact dynamically: if the forces characterising one of them become dominant, counter forces will emerge and push on in other, new, directions. For instance, advocates of liberalisation and privatisation in accordance with the free-market ideology may be so successful that the resulting inequity and overexploitation will strengthen environmentalist and fundamentalist forces. So-called ‘disaster’ or ‘doomsday’ scenarios are not included, neither are surprises. None of the scenarios include new explicit climate policies. In the original SRES report the IMAGE team elaborated the B1 marker scenario. In this scenarios the land-use related emissions were relatively more important than in the other scenarios where energy emissions dominate. The A1 narrative The A1 narrative describes a future world of strong globalisation with very rapid material growth, market capitalism, low population growth, and the rapid introduction and transfer of new and more efficient technologies. Major underlying themes are convergence among regions, capacity building and increased cultural and social interactions, with a substantial reduction in
The A2 narrative and scenario family describes a very heterogeneous world. The underlying theme is self-reliance and preservation of local identities. Fertility patterns across regions converge very slowly, which results in high population growth. Economic development is primarily regionally oriented and per capita economic growth and technological change are more fragmented and slower than in other narratives. In this scenario, globalisation slows down or reverses as nations and governments focus on cultural identity and traditional values. In large parts of the less-industrialized regions, the large and young population actively resists the ‘modernisation’ process of the last 50 years in its Western form. Autocratic, nationalist or fundamentalist regimes are one of the answers to rising social and political unrest in response to feelings of exclusion and marginalisation. However, other answers to impending crises are also experimented with, leading to a successful renaissance of traditional lifestyles or high-tech niches. The ‘cultural pluralism’ of this world may take the form of fragmentation with accompanying protectionism and conflicts; for some regions it may be the road to rediscovering and strengthening one’s own values, as in an autarchic China, an isolationist USA with its large high-tech affluence, and Africa redefined along tribal identities. The B1 narrative This scenario assumes continuing globalisation and economic growth, and a focus on the environmental and social – immaterial – aspects of life. It can be interpreted as the continuation of a balanced, transformed ‘modernisation’ process. Governance at all levels and regulated forms of market capitalism are seen as the way forward. It includes the strengthening of non-governmental organisations concerned about issues of sustainability and equity. A modest and decent world: bureaucratic, regulated, but also in search of fairness and sustainability. The B1 narrative and scenario family describes a converging world with the same low population
385 growth as in the A1 narrative. However, there are rapid changes in economic structures toward a service and information economy, with reductions in material intensity and the introduction of clean and resource-efficient technologies. The emphasis is on simultaneous global solutions to economic, social and environmental sustainability, including improved equity but no additional climate initiatives. The B2 narrative The B2 narrative and scenario family describes a world in which the emphasis is on local solutions to economic, social, and environmental sustainability. It is a world with moderate population growth, intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 narratives. While the scenario is also oriented toward environmental protection and social equity, it focuses on local and regional levels. People increasingly perceive and seize the means to manage their own situation in an equitable and sustainable manner. In some regions this may take the form of decentralised settlements on the basis of bioregions; in others, society may opt for centralised but highly energy- and material-extensive infrastructure. Some regions may develop ways to maximise the sustainable use of their indigenous renewable resources; others may shift the focus to changing socio-political structures or find ways to turn consumption into less materialistic and more spiritually and psychologically rewarding activities. At global level, initiatives may be fairly ineffective for want of global institutions – a world of good intentions but no action.
The implementation of the narratives in IMAGE 2.2 The original SRES scenarios were reported for 4 regions (OECD countries, countries in transition, developing countries in Asia, and all other countries) and the scenarios assumptions were only presented and quantified for these 4 regions. The IMAGE 2.2 implementation was performed on 17 regions. Therefore, we have used the SRES features for population, economy and final energy trajectories and disaggregated them towards these 17 regions. Starting from these data, the interpretation of the narratives involved the description of a number of regional developments in: the land use system including consumption, production and trade of agricultural products; emissions associated with agricultural production, biomass burning and waste management; Energy use and industrial activities and their emissions. Focussing on land-use emissions the following assumptions were made by the IMAGE team for the four SRES scenarios. No difference was made for A1F, A1B and A1T in the land-use related assumptions.
The A1 narrative The continuing globalization and high economic growth, with the focus on the material aspects of life, leads to a more intensive trade in agricultural products: regions like Eastern Europe and South America become larger exporting regions whereas the African regions have become food importers. The leading consumer trend is towards a higher share of animal products in diets when incomes rise. This results in a sharp increase of feed production and trade world-wide. The very high economic growth, with a convergence of industrialized and less industrialized countries, thanks to entrepreneurial dynamics and the disappearance of barriers in trade flows and movement of capital and labor, leads to a resultant rapid technology transfer. In the agricultural system this is translated with fast increasing values for the management factor, i.e. the input variable representing the difference between the theoretically feasible yield of crops, based on climate and soil conditions, and the actual yield, which is limited by less than ideal management practices, technology and know-how. Moreover, the number of food crop cycles is assumed to increase and the fertilizer use is intensified. The A2 narrative The inward, protectionist orientation and suspicion on globalization lead to a slower increase in trade of agricultural products. The continued economic growth in industrialized countries, but slow economic growth in less industrialized countries, causes an increasing gap between the poor and the rich. This gap results in a slow technology transfer, especially in the low-income regions, and therefore a slower increase of, for example, the management factor compared to the Al world. The importance of cultural identity and traditional values causes less change in the diets than in the Al world. The B1 narrative The dominant motives of the B1 narrative are orientation on quality-of-life in a broad sense expressing itself in, for example, co-operation and internal orientation, risk-aversion, and optimism with regard to human nature. This orientation leads to an increasing abatement of emissions of many polluting gases like CO, NOx and SO2 (with co-benefits for CO2 and N2O), a reduction in the wood production and a lower use of fertilizers. The high economic growth with convergence of industrialized and less industrialized countries, combined with controlled removal of barriers in trade flows, causes an increase in trade (somewhat lower than in the Al narrative, because of slower economic increase). Moreover, the increase in technology transfer leads to identical assumptions for the management factor as in the Al narrative.
386 Table 1. Assumed characteristics of the food system dynamics for the four SRES scenarios as implemented by IMAGE team (2001a). A1 Family
A2 Family
B1 Family
B2 Family
Fast increase in the volume of trade in food and feed Fast increase in food and livestock productivity
Moderate increase in the volume of trade of food and feed Moderate increase in food and livestock productivity
Moderate increase in the volume of trade of food and feed Moderate increase in food and livestock productivity
Fast increase in per capita consumption of livestock products as a result of fast GDP increase
Lowest increase in per capita consumption of livestock products as a result of lowest GDP increase
Fast increase in the volume of trade in food and feed Fast increase in food and livestock productivity with high efficiency of fertiliser use Per capita consumption of livestock products is 10% lower than A1 scenario in 2050 and 20% lower than in A1 in 2100
Moderate increase in per capita consumption of livestock products as a result of moderate GDP increase
Figure 3. Some of the indicators of the SRES scenarios. For the A1 scenarios the A1F scenario is depicted. The different colours in the energy carrier depict coal, oil, gas, biomass and others; the crop areas distinguish arable land, pastures and biomass plantations.
The B2 narrative The dominant motives are orientation on quality-of-life in a narrow sense. This also leads to reductions in emissions of polluting gases and reductions in wood production. Compared to the B1 narrative, these reductions are less because of less efficient measures in the more regionalized world of B2. The regionalized character of the B2 narrative leads to similar assumptions on the improvement of technology as for A2. For example, the management factor is assumed to increase in the same speed as in this world.
The combination of a regionalized world and a world with emphasis on sustainability and equity is translated with the lowest increase in trade of the four narratives. In summary, the food trade is maximal in the open and rich world of the Al scenario; it is slightly less in the B1 scenario, followed by the A2 scenario and finally the B2 scenario. In Table 1, the main characteristics of the food system dynamics are summarised for the four SRES narratives. In Figure 3 the most important characteristics of the four narratives are illustrated, following from the pre-described SRES data for economy and population, and resulting from
387
Figure 4. Global land cover for the 4 different SRES scenarios. (A1 upper left; A2 bottom left; B1 upper right; B2 bottom right). The red colour refers to agriculture (crops and animal husbandry), the other colours are natural vegetation.
the assumptions as implemented in the IMAGE 2.2 model.
Land use change for the different SRES scenarios Land-use change in the different SRES scenarios of IMAGE 2.2 strongly differs in the global and regional extent (Figure 4). Detailed data on land-use trends, cropping patterns, forests and natural vegetation for all scenarios and regions is given on the CD-ROM (IMAGE team, 2001a, b). Here we only summarise some major trends. In all the scenarios, the extent of land used by humans for cropping, animal husbandry, the production of biofuels increases for several decades. Only the A2 scenario shows an increasing total crop area until the end of this century, where the total crop area in other scenarios declines and, in the B1 and A1F scenarios, even reaches lower levels than in 1995 (Figure 3 and Table 2). Forestry is considered in IMAGE 2.2 but only in a secondary way. If crop area is expanded into forests, the forest products are used until the demand for wood, fibre and pulp is met. The remainder is burnt. When there is no expansion of agricultural land, the demand for timber, fibre and pulp is taken from mature woods, after which they recover again. The consequences for the carbon cycle (Net Primary Production, soil respiration and carbon fluxes due to burning) are calculated by the terrestrial carbon cycle of IMAGE 2.2 (c.f. Table 4). In the discussion below we limit ourselves to the expansion and contraction of agricultural land and forests. All scenarios show a significant increase in biomass crops to satisfy part of the energy-demand. In the scenarios with a regional focus (A2, B2) total global crop land increases, in others it remains stable (A1T and A1B) or decreases (B1 and A1F). The decrease in B1 is mainly due to rapidly increasing land productivity world-wide coupled to a lower demand due to less meat-based diets (see Figure 3). The decrease in A1F,
compared to A1T and A1B, can be explained by the fact that in the A1F scenario the energy mix is strongly based on fossil fuels, leading to a smaller increase of demand for biofuel crops. The larger crop areas in the regionalized worlds are due to the growing food demand of a larger population that is offset to a lesser extent by increasing productivities or changing diets. Land-use change in the industrialized regions (USA, Canada, Europe) shows a somewhat different development than in many earlier scenarios studies (e.g. WRR, 1992; FAO, 2000). The total area of cropland in these regions remains relatively stable in B2 and increases significantly in all other scenarios. This increase opposes the trend of the past few decades of abandoning agricultural land, which continues in many earlier scenarios. The reason behind this is the increasing demand for food by regions like China and India due to their rapid economic development and increase of population. Soon these regions may not be self sufficient in food production and start to import food at an unprecedented scale. Given the high quality of their agricultural land, Europe and the US will become larger exporting regions. Hence, the amount of agricultural land increases. This is very obvious in the scenarios that assume that global open markets will continue to develop (A1B, A1T, A1F and B1) and less in the other scenarios with the regional focus (A2 and B2). The changes in land use have consequences for the total forest area (Figure 3 and Table 3). During the first half of this century deforestation continues in all scenarios except in B1. In the A2 scenario deforestation continues throughout this century and the total forest area decreases rapidly, while in the other scenarios deforestation stops and is reversed, most prominently in the B1 and A1F scenario. Again, the larger forest area in the A1F scenario, compared to A1T and A1B is explained by the lower demand for biofuels crops in the A1F scenario. The forestation/afforestation trends here are thus strongly a function of the size, performance and structure of regional and global food markets.
Emissions, concentrations and climate change in the IMAGE-based SRES scenarios The global emissions of CO2 and other greenhouse gasses are presented in Tables 4 and 5. The factual data provided on the CD-ROM (IMAGE team, 2001a, b) specifies the emissions for all 17 regions. The scenarios range from 6 to 36 Pg CO2-equivalent per year. Different pathways are revealed. The A2 scenario shows a continuous increase in emissions to a very high level of 35 Pg CO2-equivalent1 per year. A1F (large share of fossil fuels) also continuously increases but tend to stabilise at a somewhat lower level than A2. All other scenarios peak after approximately 50 years and decrease afterwards to levels between 6 and 18 Pg CO2equivalent per year. This is mainly due to the combination of rapid technological developments and shifts
Canada USA Central America South America Northern Africa Western Africa Eastern Africa Southern Africa OECD Europe Eastern Europe Former USSR Middle East South Asia East Asia South East Asia Oceania Japan World
27.6 277.9 38.9 265.8 13.8 54.0 21.9 44.2 127.7 42.5 135.2 48.7 131.0 37.6 96.4 50.5 8.6 1422.2
Food crops
15.5 182.3 52.5 302.2 76.0 201.1 155.0 205.5 33.9 6.3 189.2 210.5 61.3 241.1 32.1 348.6 0.9 2314.1
Grass & fodder
A1F
15.7 59.1 17.8 178.3 0.0 64.1 0.6 49.9 34.8 11.6 128.6 0.0 46.1 44.5 30.6 14.4 2.4 698.5
Biofuel crops 30.0 288.3 40.0 282.0 14.3 56.7 23.2 45.4 132.3 43.0 144.7 50.0 136.3 39.2 100.1 52.9 8.9 1487.3
Food crops 16.8 188.6 53.6 311.4 76.1 205.2 156.5 208.9 35.1 6.2 189.3 213.1 60.1 248.1 32.7 347.9 1.0 2350.7
Grass & fodder
A1B
28.9 72.6 23.0 240.9 0.0 112.0 0.8 87.0 38.9 14.0 212.3 0.0 82.6 58.3 43.9 21.9 2.6 1039.7
Biofuel crops 30.0 288.3 40.0 282.0 14.3 56.7 23.2 45.4 132.3 43.0 144.7 50.0 136.3 39.2 100.1 52.9 8.9 1487.3
Food crops 16.8 188.6 53.6 311.4 76.1 205.2 156.5 208.9 35.1 6.2 189.3 213.1 60.1 248.1 32.7 347.9 1.0 2350.7
Grass & fodder
A1T
28.9 72.6 23.0 240.9 0.0 112.0 0.8 87.0 38.9 14.0 212.3 0.0 82.6 58.3 43.9 21.9 2.6 1039.7
Biofuel crops 37.5 361.7 89.6 614.8 33.9 86.4 42.5 46.5 121.1 41.8 229.4 119.8 228.6 219.5 228.3 90.5 8.3 2600.1
Food crops 21.5 261.5 117.0 679.3 69.5 308.7 272.0 351.3 42.2 7.5 240.8 207.4 87.4 505.3 77.2 388.2 1.1 3637.7
Grass & fodder
A2
16.8 70.4 19.8 169.2 0.0 40.9 0.7 49.3 37.4 12.2 108.3 0.0 55.4 41.8 32.0 13.2 2.6 669.9
Biofuel crops
Table 2. Regional extent (Mha) of agricultural land in 2100 for the different SRES Scenarios. The data are taken from IMAGE team (2001a).
24.0 232.5 37.0 208.0 16.4 53.1 23.0 41.0 105.4 37.5 121.5 50.0 124.7 41.2 91.9 45.0 8.4 1260.9
Food crops 14.9 162.8 45.2 243.9 73.4 172.5 142.5 184.6 31.0 5.7 189.2 203.0 50.6 250.6 26.7 347.3 0.9 2145.1
Grass & fodder
B1
8.9 28.5 13.4 52.9 0.0 51.2 0.7 43.8 18.5 9.7 60.9 0.0 27.7 25.2 23.2 9.6 1.3 375.4
biofuel crops
17.3 153.4 57.9 256.4 28.8 128.4 67.1 58.6 89.9 32.4 91.7 109.6 246.3 148.4 137.2 34.2 4.5 1662.2
Food crops
10.8 123.6 59.8 293.0 75.5 334.7 296.3 317.9 28.6 5.8 189.1 221.2 71.0 399.1 40.5 347.6 0.6 2815.1
Grass & fodder
B2
18.6 57.3 18.6 134.4 0.0 63.5 1.0 67.1 35.6 12.6 124.8 0.0 67.6 49.8 35.2 17.0 2.8 705.9
Biofuel crops
388
Canada USA Central America South America Northern Africa Western Africa Eastern Africa Southern Africa OECD Europe Eastern Europe Former USSR Middle East South Asia East Asia South East Asia Ocean Japan Greenland World
614.4 337.3 65.0 910.4 0.1 297.4 71.5 61.8 186.9 53.2 1292.7 16.9 76.3 112.1 244.3 155.4 25.8 2.5 4524.1
2020
636.3 292.2 70.9 880.9 0.5 314.3 101.8 100.0 132.9 53.9 1371.7 10.5 66.8 278.4 200.5 168.0 21.5 2.8 4703.9
2050
A1F
678.3 262.9 93.8 812.2 3.4 397.4 176.9 165.6 155.2 53.8 1503.2 22.7 107.5 476.2 252.2 171.3 24.8 3.9 5361.3
2100 614.0 328.8 64.1 910.9 0.1 297.9 71.0 60.9 180.3 52.8 1291.0 16.3 73.4 95.8 244.8 155.1 25.6 2.5 4485.5
2020 625.8 281.0 68.2 843.3 0.5 270.4 101.3 55.1 127.4 48.8 1321.4 10.4 47.1 258.8 184.8 159.1 20.8 2.8 4426.9
2050
A1B
661.8 241.4 86.3 738.0 3.0 352.9 172.8 141.9 145.2 51.1 1417.8 19.6 80.5 449.8 238.0 161.2 24.2 3.9 4989.4
2100
Table 3. Regional extent of forest (Mha) in the different SRES scenarios.
613.9 324.0 63.6 910.0 0.1 297.5 70.7 60.7 177.7 52.3 1289.2 17.1 73.4 90.5 240.5 154.8 25.3 2.5 4464.0
2020 622.3 273.2 65.9 858.7 0.5 268.7 100.9 47.2 127.2 46.7 1324.3 10.1 39.7 249.7 178.2 156.0 20.4 2.8 4392.4
2050
A1T
657.9 231.0 83.9 763.9 3.0 348.5 170.2 137.6 146.0 48.9 1424.8 16.8 78.3 437.7 232.1 159.2 24.1 3.8 4967.6
2100 604.9 286.0 52.5 810.7 0.1 275.2 53.5 44.5 188.8 52.6 1311.1 8.7 77.4 84.8 258.7 131.0 27.2 2.5 4270.4
2020 630.0 280.2 21.5 708.2 0.2 219.1 46.8 20.5 172.1 56.9 1333.9 1.9 49.7 91.3 196.5 145.1 25.1 2.8 4001.7
2050
A2
655.6 151.5 13.0 203.9 0.5 304.5 77.6 83.3 149.1 52.8 1383.6 1.9 32.8 88.4 96.9 102.5 24.7 3.8 3426.4
2100 611.4 340.8 65.9 926.8 0.1 300.3 73.9 70.9 192.8 55.4 1316.9 16.9 87.3 134.8 257.5 147.8 25.3 2.5 4627.4
2020 645.3 347.5 76.7 969.3 0.8 321.2 112.8 105.4 169.3 58.2 1405.5 12.2 78.6 288.6 220.2 171.3 23.0 2.8 5008.7
2050
B1
680.2 325.9 96.5 1000.4 4.3 411.3 175.0 180.3 192.0 61.0 1543.6 21.1 129.3 459.0 262.3 177.1 26.0 3.4 5748.8
2100
608.4 305.3 63.4 889.4 0.1 273.1 52.9 52.5 198.4 57.2 1330.3 13.2 46.5 73.8 240.4 146.8 26.8 2.5 4381.1
2020
635.6 367.2 56.8 915.2 0.3 199.7 46.2 21.7 190.6 61.0 1375.6 7.8 12.1 203.7 181.5 162.7 23.3 2.8 4463.9
2050
B2
685.4 410.8 68.7 860.5 0.3 224.7 45.7 84.7 193.1 63.4 1526.6 1.0 21.6 207.8 203.8 178.3 28.8 3.6 4809.0
2100
389
390 Table 4. Land-use emissions for the different SRES scenarios in IMAGE 2.2. Year
A1F
A1B
A1T
A2
B1
B2
Carbon dioxide emissions from deforestation (Pg C per year) 2020 0.98 1.04 1.10 1.58 0.95 1.61 2050 1.18 1.89 1.67 0.97 0.64 0.56 2100 0.00 0.00 0.00 2.71 0.00 0.08 Carbon dioxide emissions from fuel woods (Pg C per year) 2020 0.50 0.48 0.46 0.54 0.50 0.22 2050 0.48 0.49 0.46 0.62 0.44 0.48 2100 0.30 0.24 0.28 0.52 0.26 0.74 Carbon dioxide emissions from timber, fibre and pulp decay (Pg C per year) 2020 0.30 0.30 0.30 0.27 0.30 0.48 2050 0.69 0.69 0.69 0.44 0.38 0.36 2100 2.02 1.82 1.84 0.72 0.74 0.32 Carbon dioxide emissions from forest regrowth after timber extraction or abandonment of agricultural land (Pg C per year)a 2020 )0.83 )0.81 )0.77 )0.77 )0.81 )0.89 2050 )2.53 )2.15 )2.03 )1.17 )2.79 )1.85 2100 )4.86 )4.10 )3.76 )1.99 )3.56 )2.43 Methane emissions from land-use sources (Tg CH4 per year) 2020 280 280 280 286 262 276 2050 356 355 357 392 291 323 2100 322 322 322 573 224 332 Nitrous oxide from land-use sources (Tg N per year) 2020 6.5 6.5 6.6 6.4 5.8 6.2 2050 8.4 8.7 8.7 8.6 6.8 7.1 2100 6.6 6.8 6.8 12.7 5.2 7.4 a
Negative emissions denote an uptake.
to other energy sources. The B1 scenario shows the lowest emission levels at 70% of current levels. The energy and industry emissions of methane are in the same order of magnitude as the land-use emissions (Table 4 and 5) but there is a large level of natural emissions. In IMAGE we have not specified those emissions but assumed them constant over time. This is a coarse approximation because these natural emissions are influenced by climate and soil properties. The land-use related nitrous oxide emissions stem from application of synthetic N fertilisers and animal wastes to cropland and grasslands, animal waste management systems, grazing, soil incorporation of crop residues and cultivation of leguminous crops, as well as indirect sources caused by leaching of N and by human sewage. All these sources are calculated on the basis of the IPCC Methodology for National GHG emission Inventories (IPCC, 1997) as implemented by Mosier et al. (1998). The assessment of nitrous oxide emissions from soils under natural vegetation is based on a modification of the regression model developed by Bouwman et al. (1993) and Kreileman and Bouwman (1994). The regression now includes the most recent measurement data and explains about 70% of the variability in reported measurements. Total N2O emissions from soils under natural vegetation and oceans are about 9 Tg N2O-N yr)1.
Table 5. Total emissions for the different SRES scenarios in IMAGE 2.2. Year
A1F
A1B
A1T
A2
B1
B2
Carbon dioxide emissions from energy use (Pg C per year) 2020 11.49 11.22 10.78 9.78 8.93 9.58 2050 22.48 19.02 16.15 16.31 11.49 11.32 2100 26.29 15.07 9.37 26.45 5.16 11.24 Total Carbon dioxide emissions from all human sources (Pg C per year) 2020 12.9 12.6 12.5 11.9 10.1 11.6 2050 23.0 20.4 17.2 17.5 10.5 11.3 2100 24.3 13.7 8.3 28.9 2.6 10.5 Net Carbon dioxide from natural sources and sinks (Pg C /yr) 2020 )2.4 )2.4 )2.3 )2.2 )2.3 )2.2 2050 )4.5 )4.2 )3.7 )3.3 )3.1 )3.1 2100 )4.8 )3.5 )2.8 )3.0 )1.9 )2.9 Methane from all sources (Tg CH4 per year)a 2020 662 662 658 667 608 650 2050 830 819 782 841 648 729 2100 746 667 629 1094 402 699 Nitrous oxide from all human sources (Tg N per year) 2020 7.3 7.3 7.3 7.2 6.3 6.9 2050 9.4 9.7 9.6 9.4 7.3 7.7 2100 7.7 7.7 7.5 13.9 5.6 8.2 Nitrous oxide from natural sources (Tg N per year) 2020 10.5 10.6 10.6 10.6 10.5 10.6 2050 11.9 11.9 11.8 11.6 11.5 11.6 2100 13.7 13.1 12.5 13.5 11.9 12.7 Total Nitrous oxide emissions (Tg N per year) 2020 17.8 17.9 17.8 17.8 16.9 17.5 2050 21.3 21.5 21.3 21.1 18.8 19.4 2100 21.3 20.8 20.1 27.3 17.4 20.8 a This includes a constant annual natural emission source of 230 Tg CH4.
The global emissions from agricultural, industrial and energy-related sources is 5.3 Tg N2O-N yr)1, and the computed increase of N2O emissions caused by climatic change is 0.3 Tg N2O-N during the past 3–4 decades. The total anthropogenic emission of 5.7 Tg N2O-N yr)1 is in line with estimates of the anthropogenic emission based on mass-balance calculations of Bouwman et al. (2000). Direct application of the estimates of Mosier et al. (1998) would lead to an important overestimate of the anthropogenic emission and the global N2O budget. The SRES scenarios have also specified the future of sulphur emissions and the consequent aerosols load in the atmosphere. Although these substances remain relatively short in the atmosphere, they regionally have a cooling effect. In earlier IPCC scenarios this effect reduced the temperature increase. In SRES it is assumed that in all narratives sulphur emissions decline rapidly because of their threat to public health. This trend is apparent over the last decade in industrialised countries, but has also started in heavily polluted but rapidly developing regions, such as China. The cooling effect in the SRES scenarios therefore disappears during this century.
391
Figure 5. Global CO2 concentrations (left) and CO2-equivalent concentrations (right) for the 6 SRES scenarios. (The scenarios are: B1 green; A1B black; A1F light blue; A1T yellow; A2 red; and B2 dark blue).
Figure 6. Global mean temperature increase (left) and sea-level rise (right) for the 6 SRES scenarios. (The scenarios are: B1 green; A1B black; A1F light blue; A1T yellow; A2 red; and B2 dark blue).
All these emission scenarios lead to strongly increasing concentrations of greenhouse gases in the atmosphere (Figure 5). Only the B1 and A1T tend to level off at the end of this century due to rapidly decreasing emissions. This continuous increase is a consequence of the slow uptake of approximately 50% of current CO2 emissions in the oceans and the biosphere. The other 50% remains in the atmosphere, thereby increasing concentrations. Emissions have to be halved before concentration stabilisation is reached. The global mean temperature increase ranges between 1.9 and 3.3 °C for the period 1990–2100 for all these scenarios and continues to increase, although there is a slight tendency for levelling off in B1 and A1T (Figure 6). This range is lower than the reported range by the 2001 IPCC report (1.8–5.8 °C). We have used the median value of the climate sensitivity (2.5 °C). When we use also the full range of the climate sensitivity (1.5– 4.5 °C for a doubling of CO2-equivalent forcing), then our range is only slightly lower (1.2–4.9 °C). This difference is mainly due to differences in interactions between land, climate and the carbon cycle, which are not considered in determining the IPCC range. The resultant of all these interactions is a slower increase in atmospheric GHG concentrations. There is less difference for sea-level rise (55–70 cm) among the scenarios. All scenarios show a continuous increase and there is no tendency to level of yet. This is partly due to the large time lags in the drivers of sealevel rise (thermal expansion and melting ice sheets). Larger differences can be expected in the 22nd century or even in the centuries there after.
Interactions and feedbacks IMAGE 2.2 provides more consistent emission estimates than the original SRES scenarios because not only emissions are addressed but also simultaneously the resulting climate change and impacts. This is important for determining the interactions in the biogeochemical cycles and climate system that determine the final buildup of greenhouse gases in the atmosphere. The changing climate also influences land-use patterns, which, in turn, alter emissions. A proper treatment of these interactions is therefore one of the main reasons to develop an integrated model. The reader is referred to Leemans et al. (2002) for a complete sensitivity analysis of different parameters determining the build-up of atmospheric CO2 concentrations. The land-use dynamics described above strongly determines the global and regional fluxes of carbon and other greenhouse gases. Globally the mature undisturbed natural vegetation continued to function as a sink (Figure 7). This sink function initially increases under a changing climate and increasing atmospheric CO2 concentrations, it peeks around 2050 and is then somewhat reduced. This is consistent with analysis from other modelling groups (Cramer et al., 1999). Another class of forests is the regrowing forests. This is either abandoned agricultural land or forests that have been harvested for timber and return back towards their natural state. These forests are thus generally young and start to store carbon after a short period of intensified soil respiration, as clearly can be seen from Figure 7.
392
Figure 7. Ecosystem fluxes in the different scenarios (Left panel: natural vegetation; Middle panel: regrowing vegetation and Right panel: deforestation) (The scenarios are: B1 green; A1B black; A1F light blue; A1T yellow; A2 red; and B2 dark blue).
The forestation/deforestation fluxes in IMAGE result thus from a complex interplay between land use, derived from regional demand and supply of food, fibre and fuelwoods, trade and a series of biophysical properties of land locally. Another indicator for the global carbon cycle is Net Primary Production (NPP) and Net Ecosystem Production, which is NPP minus heterotrophic soil respiration (Figure 8). In all scenarios NPP increases as a function of the changing land uses, climate and atmospheric CO2 concentrations. It levels of in the B1 scenario, where all these factors level off. Soil respiration also increases in all scenarios. The sink function of the biosphere as a whole (a larger negative NEP) is enhanced in most scenarios. An interesting result, however, is that in the A2 scenario with the highest CO2-concentrations and temperature increase, this sink strength rapidly declines. This could indicate that the functioning of the biosphere is being altered and that beyond this century the biosphere could well become a source instead of a sink in scenarios with strong climate change. Another explanation is the actual land-use changes. In the A2 scenario the amount of deforestation is largest. This results in a small extent of forests and thus reduced NPP. In the A1F scenario CO2 concentrations are high, which enhances growth (CO2 fertilisation and enhanced water use efficiency) and deforestation slows down and eventually stops at the end of this century. The extent of forests is somewhat larger than today. Here we see that
the biosphere rapidly sequesters carbon. Land use thus seems more important in determining the biosphere sink than the interactions related to climate.
Concluding remarks The SRES scenarios were a major milestone in scenario development with the incorporation of quantitative narratives. These narratives enhance the applicability of the scenarios and assists in enhancing the resolution whenever needed. Unfortunately, the weakest aspect of SRES was the estimations of land-use emissions. Here we have presented an update of the land use emissions with the improved version of the IMAGE 2 model. This implementation of the SRES scenarios provide for 17 regions emissions of different land-use activities. The paper has presented and discussed some of the results, but all the data is brought together in an easy-to-use user support system on CD-ROM (IMAGE team 2001a, b). Also a data link to MS-Excel is created. This allows many users to apply and visualise the SRES data for their own analyses. The main advantage of these IMAGE results is the fact that the land-use emissions are not just estimated but that the simultaneous impacts of enhanced CO2 concentrations and climate change on crop growth, land use and ecosystems are incorporated. These impacts strongly influence land-use patterns and thus land-use emissions. Our analysis further shows that the easy-to-
Figure 8. Global Net Primary Productivity (Pg C/yr) and soil respiration (Pg C/yr) and the net carbon flux for the different scenarios. (The scenarios are: B1 green; A1B black; A1FI light blue; A1T yellow; A2 red; and B2 dark blue).
393 calculate land-use emissions are not the only aspect to consider. Especially the natural fluxes of CO2, CH4 and N2O are very sensitive to land use change and climate, as is shown in the comparison between the scenarios A2 and A1F. In the latter, the biosphere is a large sink, which rapidly disappears in A2. The difference is mainly caused by the impacts of land use on the terrestrial carbon cycle. Most models used for the SRES development did not consider land use and feedbacks and focussed strongly on energy emissions. For fossil-fuel related energy emissions, the impact of interactions is not important. The carbon in fossil fuels is sequestered eras ago and now emitted to the atmosphere, where it enters the carbon cycle. The triviality of interactions in determining energy-use related emissions, rapidly changes when other than fossil energy sources are considered. In almost all SRES scenarios there is a strong reliance on modern biofuels and other renewables. The production of these fuels requires land and thus links to land use emissions (Tables 3 and 4). In energy scenarios that assume large amounts of renewables, land use aspects and systemic interactions in the society-biosphereatmosphere must be considered if realistic emissions estimates have to be developed. In conclusion, the IMAGE 2.2 CD-ROM provides a comprehensive implementation of all SRES scenarios with not only improved emissions estimates from landuse, energy use and industrial activities for all GHGs and sulphur, but also the resulting concentrations, climate change and impacts. As such it is a landmark in comprehensive scenario development.
Endnotes 1
CO2 -equivalent is a measure to present the impact on radiative forcing of all greenhouse gases in terms of CO2. The CO2 equivalent values are generally 20–30% higher than the CO2 values.
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