The share of GHG emissions from Asian regions, that is, from Japan, China, India, and ‘Other Asia,’ also changes remarkably, rising from only 25 % in 1990 to about 40 % in 2020. By country, the GHG emissions grow fast in China and India, reaching 4- and 4.5-fold the 2005 levels by 2050, respectively. Fig. 5 GHG emissions in the reference scenario. Note GHG emissions are calculated as the weighted sum of CO2, CH4, N2O, HFC, PFC, and SF6, using the 100-year Global Warming Potentials. Emissions from 1990 to 2005 are calculated using the

EDGAR v4.1 emission database (European Commission et al. 2010) Achievability of the target Ulixertinib and required GHG emission reduction In this section we ask two questions: “Will it be technically possible to achieve a 50 % reduction

of GHG emissions by 2050 relative to the 1990 level?” and if so, “What emission reduction will be required in major countries in the mid- and long-term?” We address these questions using marginal abatement cost Selleck Adriamycin (MAC) curves. Developing the MAC curves A MAC curve depicts the relationship between the MAC and emission reduction in a region and year in question. To develop MAC curves here, we use the simulation results of GHG price path scenarios in which GHG emissions are estimated along an externally fixed GHG emission price path. The GHG emission price in these price scenarios is theoretically equal to a MAC of GHG emission. Hence, we develop the MAC curves using the relationship between the GHG emission Inositol monophosphatase 1 price and GHG emission reduction in GHG price path scenarios relative to the reference scenario. Note that GHG emission trading among the regions does not take place in GHG price path scenarios. Therefore, the MAC curves developed in this study represent the relationship between the MAC and GHG emission

reduction within the region. Figure 6 illustrates how the MAC curves are developed for this study. Fig. 6 Methodology for developing MAC curves in this study MAC curves are developed in two steps: (1) simulate GHG emissions in each GHG price path scenario (see Fig. 6b), (2) draw the MAC curve by plotting GHG emission change rates (R) and the corresponding carbon prices (P) (see Fig. 6c). Analysis using MAC curves Figure 7 shows MAC curves estimated for six major regions and the world in 2020 and 2050. The MAC curve for each region can be characterized by the x-intercept and slope of the curve. The x-intercept represents the GHG emission change rate relative to 1990 in the reference scenario, in which the GHG price is $0/tCO2-eq. The slope of the curve represents the sensitiveness of GHG emissions to the MAC: the milder the slope, the larger the GHG emission reduction when the MAC increases. In 2050, MAC curves for China and India have very high x-intercepts and remarkably mild slopes, especially in the lower MAC range.