Also in this chapter:
The implications of 2020 emission levels for long-term temperature outcomes depend importantly on how much and how fast it is considered feasible to reduce emissions before, and particularly beyond 2020. Feasibility (i.e. considerations on whether a particular emission pathway is possible to achieve) is a subjective concept that has to take into account several factors: technological, economic, political and social. Technological feasibility refers to whether technologies exist, and can be scaled-up fast enough, to produce enough low-carbon energy to meet demand. Economic feasibility refers to whether or not the cost of doing so is considered prohibitively high. Political feasibility includes factors, such as whether the assumed extent of participation in emission reduction efforts across countries (or economic sectors) is plausible and whether the time required to develop institutions that would facilitate this participation is reasonable. Finally, social feasibility refers to whether measures to control emissions would be acceptable to society, for example after taking into account their implications for equity or for non-climate environmental consequences.
IAMs can account for several of these factors by representing inertia of technological and social systems. Examples include assumptions about the maximum feasible technology penetration rates, maximum cost, feasibility of specific system configurations, and maximum speed of behavioural changes.
The results of IAMs are, therefore, helpful in informing our view on feasibility and, hence, are the primary source of quantitative information used in this assessment. However, it should be noted that they do not set “hard laws” on feasibility. On the one hand, they are based on our current understanding of technological and economic constraints, which could change; therefore the range of emission pathways considered feasible could shrink or expand over time. For instance, the models do not include the possibility of the development of “game-changing” new technologies currently unforeseen. On the other hand, feasibility also depends on societal and political factors that are not typically considered in IAMs (Bosetti et al. 2010, Ha-Duong et al. 1997, Ha-Duong and Treich 2004). Recently, IAM studies have explored the influence of participation of different countries in model comparison studies (Clarke et al. 2009) and this could reduce the range of pathways considered feasible.
One important factor determining the maximum emission reduction rate is the lifetime of machinery and infrastructure: this can be decades or even centuries for building stock and urban infrastructure; around 40 years for power stations; 20 to 40 years for manufacturing equipment; up to 20 years for heating devices; and 10 to 20 years for passenger vehicles, but much longer for transport infrastructure (Philibert 2007). These lifetimes are critically important, if mitigation strategies aim to avoid premature replacement of capital and the high costs associated with it. For illustration, carbon dioxide emissions from energy and industry would decline by about 3 per cent per year if no new emission-producing infrastructure were to be built (adapted from Davis et al. 2010). In the assessed IAM literature on mitigation scenarios, the highest average rate of total emission reduction over the next 4 to 5 decades is about 3.5 per cent per year (den Elzen et al. 2010)25.
To put this in context, a global CO2 emission reduction rate of 3 per cent would require a rate of decrease in emissions per unit of GDP (or decarbonization rate) of almost 6 per cent for an assumed annual rate of global GDP growth of 3 per cent. Ranger et al. (2010) show that there is very little precedent for such high rates of emission reductions amongst the top 25 emitters. The global decarbonization rate over the 1969-2009 period was 1 per cent on average, although this was in the absence of strong international climate policies. In a society that places the highest possible priority on reducing emissions, the normal capital turnover rate could possibly be increased. However, some studies suggest that higher annual reduction rates of up to about 6 per cent per year are possible for a limited time in certain circumstances, but only when the conditions have been put in place for rapid investment in decarbonization of the energy sector (e.g. Edenhofer et al. 2009). The feasibility of achieving emission reduction rates of 3 per cent or more per year for CO2 emissions from energy and industry is highly uncertain, given political and societal constraints and the fact that emission reductions are not likely to be distributed evenly across nations.
Lastly, it should be noted that most of the pathways consistent with the temperature limits in this report include negative global emissions of CO2 from energy and industry beginning in the 2060s and 2070s. Understanding the feasibility of negative emissions is therefore crucial for assessing the chances of meeting the 2° C and 1.5° C temperature limits: if negative emissions of a significant scale are not possible, then our options for meeting the targets are significantly constrained. Global net negative emissions occur when the removal of CO2 from the atmosphere due to anthropogenic activities is greater than the anthropogenic emissions into it. One way to achieve this (and assumed by many IAMs) is through the implementation of bioenergy combined with carbon capture and storage (BECCS). This involves using large amounts of biomass to generate energy, and then capturing and safely storing underground or elsewhere CO2 released by combustion. Since biomass takes up CO2 from the atmosphere in the course of its growth, and since the CO2 taken up is stored underground, BECCS in effect removes CO2 from the atmosphere (Azar et al. 2010). Direct air capture of CO2 and other technologies may also lead to negative emissions, but are currently not included in IAMs. The feasibility of large scale bioenergy systems, whether used in conjunction with CCS or not, is related to factors such as availability of land and water, impacts on biodiversity, and biomass productivity.