126.96.36.199 Anthropogenic land emissions and sequestration
Some of the first global integrated assessment scenario analyses to account for land-use-related emissions were the IS92 scenario set (Leggett et al., 1992) and the SRES scenarios (Nakicenovic et al., 2000). However, out of the six SRES models, only four dealt with land use specifically (MiniCAM, MARIA, IMAGE 2.1, AIM), of which MiniCAM and MARIA used more simplified land-use modules. ASF and MESSAGE also simulated land-use emissions, however ASF did not have a specific land-use module and MESSAGE incorporated land-use results from the AIM model (Nakicenovic et al., 2000). Although SRES was a seminal contribution to scenario development, the treatment of land-use emissions was not the focus of this assessment; and, therefore, neither was the modelling of land-use drivers, land management alternatives, and the many emissions sources, sinks, and GHGs associated with land.
While some recent assessments, such as UNEP’s Third Global Environment Outlook (UNEP, 2002) and the Millennium Ecosystem Assessment (Carpenter et al., 2005), have evaluated land-based environmental outcomes (global environment and ecosystem goods and services respectively), the Energy Modelling Forum’s 21st Study (EMF-21) was the first large-scale exercise with a special focus on land as a climate issue. In EMF-21, the integrated assessment models incorporated non-CO2 greenhouse gases, such as those from agriculture, and carbon sequestration in managed terrestrial ecosystems (Kurosawa, 2006; Van Vuuren et al., 2006a; Rao and Riahi, 2006; Jakeman and Fisher, 2006). A few additional papers have subsequently improved upon their EMF-21 work (Riahi et al., 2006; Van Vuuren et al., 2007). In general, the land-use change carbon emissions scenarios since SRES project high global annual net releases of carbon in the near future that decline over time, leading to net sequestration by the end of the century in some scenarios (see Figure 3.10). The clustering of the non-harmonized post-SRES scenarios in Figure 3.10 suggests a degree of expert agreement that the decline in annual land-use change carbon emissions over time will be less dramatic (slower) than suggested by many of the SRES scenarios. Many of the post-SRES scenarios project a decrease in net deforestation pressure over time, as population growth slows and crop and livestock productivity increase; and, despite continued projected loss of forest area in some scenarios (Figure 3.7), carbon uptake from afforestation and reforestation result in net sequestration.
Figure 3.10: Baseline land-use change and forestry carbon net emissions.
There also seems to be a consensus in recent non-CO2 GHG emission baseline scenarios that agricultural CH4 and N2O emissions will increase until the end of this century, potentially doubling in some baselines (see Table 3.1; Kurosawa, 2006; Van Vuuren et al., 2006a; Rao and Riahi, 2006; Jakeman and Fisher, 2006; Riahi et al., 2006; Van Vuuren et al., 2007). The modelling of agricultural emission sources varies across scenarios, with livestock and rice paddy methane and crop soil nitrous oxide emissions consistently represented. However, the handling of emissions from biomass burning and fossil fuel combustion are inconsistent across models; and cropland soil carbon fluxes are generally not reported, probably due to the fact that soil carbon sequestration mitigation options are not currently represented in these models.
Table 3.1: Baseline global agricultural non-CO2 greenhouse gas emissions from various long-term stabilization scenarios (GtCO2-eq).
|Scenario ||Non-CO2 GHG agricultural emissions sources represented* ||GtCO2-eq |
|CH4 ||N2O |
|2000 ||2020 ||2050 ||2070 ||2100 ||2000 ||2020 ||2050 ||2070 ||2100 |
|GTEM-EMF21 ||Enteric, manure, paddy rice, soil (N2O) ||2.09 ||2.88 ||4.28 ||nm ||nm ||1.95 ||2.60 ||3.64 ||nm ||nm |
|MESSAGE-EMF21 ||Enteric, manure, paddy rice, soil (N2O) ||2.58 ||3.42 ||6.05 ||6.00 ||5.06 ||2.57 ||3.48 ||4.65 ||3.79 ||2.32 |
|IMAGE-EMF21 ||Enteric, manure, paddy rice, soil (N2O and CO2), biomass & agriculture waste burning, land clearing ||3.07 ||4.15 ||4.34 ||4.37 ||4.55 ||2.02 ||2.75 ||3.11 ||3.23 ||3.27 |
|GRAPE-EMF21 ||Enteric, manure, paddy rice, soil (N2O), biomass & agricultural waste burning ||2.59 ||2.65 ||2.85 ||2.82 ||2.76 ||2.79 ||3.31 ||3.84 ||3.93 ||4.06 |
|MESSAGE-A2r ||Enteric, manure, paddy rice, soil (N2O) ||2.58 ||3.43 ||4.78 ||5.52 ||6.57 ||2.57 ||3.48 ||4.37 ||4.77 ||5.22 |
|IMAGE 2.3 ||Enteric, manure, paddy rice, soil (N2O and CO2), biomass & agricultural waste burning, land clearing ||3.36 ||3.95 ||4.41 ||4.52 ||4.46 ||2.05 ||2.48 ||2.93 ||3.07 ||3.06 |
As noted in Section 188.8.131.52 climate change feedbacks could have a significant influence on long-term land use and, to date, are only partially represented in long-term modelling of land scenarios. Similarly, climate feedbacks can also affect land-based emissions. For instance, rising temperatures and CO2 fertilization can influence the amount of carbon that can be sequestered by land and may also lead to increased afforestation due to higher crop yields. Climate feedbacks in the carbon cycle could be extremely important. For instance, Leemans et al. (2002) showed that CO2 fertilization and soil respiration could be as important as the socio-economic drivers in determining the land-use emissions range.
In addition, potentially important additional climate feed-backs in the carbon-climate system are currently not accounted for in integrated assessment scenarios. Specifically, new in-sights suggest that soil drying and forest dieback may naturally reduce terrestrial carbon sequestration (Cox et al., 2000). However, these studies, as well as studies that try to capture changes in climate due to land-use change (Sitch et al., 2005) have thus far not been able to provide definitive guidance. A modelling system that fully couples land use change scenarios with a dynamic climate-carbon system is required in the future for such an assessment.