1

RCP4.5: A Pathway for Stabilization of 

Radiative Forcing by 2100

Allison M. Thomson*, Katherine V. Calvin, Steven J. Smith, G. Page Kyle, April Volke, 

Pralit Patel, Sabrina Delgado-Arias, Ben Bond-Lamberty, Marshall A. Wise, Leon E. Clarke 

and James A. Edmonds

Joint Global Change Research Institute, Pacific Northwest National Laboratory and the 

University of Maryland, 5825 University Research Court, College Park, MD 20740.

* Corresponding author: Allison.thomson@pnl.gov; phone (301-314-6750); fax (301-

314-6719). 

ABSTRACT

Representative Concentration Pathway (RCP) 4.5 is a scenario that stabilizes 

radiative forcing at 4.5 Watts per meter squared in the year 2100 without 

ever exceeding that value. Simulated with the Global Change Assessment 

Model (GCAM), RCP4.5 includes long-term, global emissions of greenhouse 

gases, short-lived species, and land-use-land-cover in a global economic 

framework. RCP4.5 was updated from earlier GCAM scenarios to incorporate 

historical emissions and land cover information common to the RCP process 

and follows a cost-minimizing pathway to reach the target radiative forcing. 

The imperative to limit emissions in order to reach this target drives changes 

in the energy system, including shifts to electricity, to lower emissions energy 

technologies and to the deployment of carbon capture and geologic storage

technology. In addition, the RCP4.5 emissions price also applies to land use 

emissions; as a result, forest lands expand from their present day extent. The 

simulated future emissions and land use were downscaled from the regional 

simulation to a grid to facilitate transfer to climate models. While there are 

many alternative pathways to achieve a radiative forcing level of 4.5 W m-2, 

the application of the RCP4.5 provides a common platform for climate models 

to explore the climate system response to stabilizing the anthropogenic 

components of radiative forcing. 

Keywords: climate change mitigation; Integrated Assessment; Global Change 

Assessment Model; Representative Concentration Pathway; scenario.
2

1. INTRODUCTION

Representative Concentration Pathway (RCP) 4.5 is a scenario of long-term, 

global emissions of greenhouse gases, short-lived species, and land-use-landcover which stabilizes radiative forcing at 4.5 Watts per meter squared (W m2, approximately 650 ppm CO2-equivalent) in the year 2100 without ever 

exceeding that value. The defining characteristics of this scenario are 

enumerated in Moss et al. (2008, 2010). RCP 4.5 is based on the MiniCAM 

Level 3 stabilization scenario reported in Clarke, et al. (2007) with additional 

detail on the non-CO2 and pollution control assumptions in Smith and Wigley 

(2006), and incorporating updated land use modeling and terrestrial carbon 

emissions pricing assumptions as reported in Wise et al (2009a,b).

Unlike the scenarios developed by the IPCC and reported in Nakicenovic et al. 

(2000), which examined possible global futures and associated greenhouserelated emissions in the absence of measures designed to limit anthropogenic 

climate change, RCP 4.5 is a stabilization scenario and assumes that climate 

policies, in this instance the introduction of a set of global greenhouse gas 

emissions prices, are invoked to achieve the goal of limiting emissions, 

concentrations and radiative forcing.

While RCP 4.5 is based on the “MiniCAM Level 3” scenario reported in Clarke

et al. (2007), RCP 4.5 differs in several important regards. First, the Clarke et 

al. (2007) scenario considered a slightly different definition of radiative 

forcing than RCP 4.5. In Clarke et al. (2007), radiative forcing is defined in 

terms of a suite of six greenhouse gases, carbon dioxide (CO2), methane 

(CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons 

(PFCs) and sulfur hexafluoride (SF6). RCP 4.5 considered the influences of a 

broader set of anthropogenic emissions including CO2, CH4, N2O, HFCs, PFCs, 

and SF6, but also chemically active gases such as carbon monoxide (CO) and 

volatile organic compounds (VOCs). Importantly, RCP 4.5 considers the 

influence of sulfur aerosols, as well as black and organic carbon. The Clarke 

et al. (2007) scenario stabilized radiative forcing at approximately 4.7 W m-2

while RCP stabilizes radiative forcing at 4.5 W m-2. For CO2, the most 
3

important anthropogenically released greenhouse gas, year 2100 

concentrations are somewhat higher in the Clarke et al. (2007) scenario, 

approximately 550 ppm CO2, than in RCP 4.5, approximately 525 ppm CO2. 

RCP 4.5 also employed updated historical data series, calibration to the year 

2000 consensus emissions inventories from Lamarque et al. (2010), and a 

new representation of residue biomass supply (Gregg and Smith 2010). 

More importantly, RCP 4.5 employed a more sophisticated land-use and landcover model (Wise et al. 2009a,b) than was available for use in Clarke et al.

(2007). Perhaps the most important difference between Clarke et al. (2007)

and RCP 4.5 is the downscaling of emissions and land-use-land-cover from 

the 14 geopolitical GCAM regions to a 0.5 degree grid for the RCPs in order to 

enable use of the scenario in global climate models. Finally, RCP 4.5 takes 

advantage of one technology that was not modeled in Clarke et al., namely 

combining bioenergy production with CO2 capture and geologic storage 

(CCS). This technology combination is capable of producing final energy such 

as electricity with net-negative carbon emissions. 

Because the RCPs are based on scenarios documented in the open literature, 

each reflects a different set of underlying socioeconomic assumptions. RCP 

4.5 is a stabilization scenario and thus assumes the imposition of emissions 

mitigation policies. RCP 4.5 is derived from its own “reference”, or “noclimate-policy”, scenario. This reference scenario is unique to RCP 4.5 and 

differs from RCP 8.5 as well as from the reference scenarios associated with 

RCP 6.0 and RCP 2.6.

In the remainder of this paper we will discuss the modeling environment 

employed to develop RCP 4.5, the Global Change Assessment Model (GCAM), 

which was used to transform the original MiniCAM Level 3 scenario (Clarke 

et al., 2007) into RCP 4.5. We will then proceed to describe the underlying 

socioeconomic assumptions that shape RCP 4.5 and its associated reference

scenario and discuss the characteristics of RCP 4.5, highlighting the global 

energy, economic, land use, and land cover systems, as well as the 

mechanisms employed to limit radiative forcing to 4.5 W m-2 and contrast 

RCP 4.5 to its reference scenario. 
4

2. METHODS

2.1 The Global Change Assessment Model

The GCAM is a global integrated assessment model and a direct descendent of 

the MiniCAM model (Kim et al., 2006; Clarke et al., 2007; Brenkert et al.,

2003). It combines representations of the global economy, energy systems, 

agriculture and land use, with representation of terrestrial and ocean carbon 

cycles, a suite of coupled gas-cycle, climate, and ice-melt models. GCAM 

tracks emissions and concentrations of greenhouse gases and short-lived

species including CO2, CH4, N2O, NOx, VOCs, CO, SO2, carbonaceous aerosols, 

HFCs, PFCs, and SF6. 

GCAM is a dynamic recursive economic model driven by assumptions about 

population size, and labor productivity that determine potential gross 

domestic product in each of 14 regions at 15 year time steps. GCAM 

establishes market-clearing prices for all energy, agriculture and land 

markets such that supplies and demands for all markets balance 

simultaneously. The GCAM energy system includes primary energy 

resources, production, energy transformation to final fuels, and the 

employment of final energy forms to deliver energy services such as 

passenger kilometers in transport or space conditioning for buildings. GCAM 

contains detailed representations of technology options in all of the economic 

components of the system with technology choice determined by market 

competition. 

The agriculture and land use component is fully integrated with the GCAM 

economic and energy system components. Land is allocated between 

alternative uses based on expected profitability, which in turn depends on 

the productivity of the land-based product (e.g. mass of harvestable product 

per ha), product price, and non-land costs of production (labor, fertilizer, 

etc.). The productivity of land-based products is subject to change over time 

based on future estimates of crop productivity change. We adopt 

assumptions for the next 30 years based on those employed by the UN Food 
5

and Agricultural Organization (Bruinsma, 2003). A full description of the 

agriculture and land use modeling in GCAM as used for RCP4.5 can be found 

in Wise et al. (2009a).

The GCAM physical atmosphere and climate are represented by the Model for 

the Assessment of Greenhouse-Gas Induced Climate Change (MAGICC; Wigley 

and Raper 1992, 2002; Raper et al., 1996). To construct the RCP4.5 scenario, 

we use MAGICC version 5.3, which is initialized to the IPCC 4th Assessment 

Report.1 The definition of total radiative forcing for the RCP4.5 does not 

include albedo, nitrate, and mineral dust. These three forcing agents have a 

fixed future forcing of -0.4 W m-2 in MAGICC version 5.3. 

The RCP4.5 stabilization scenario is a cost-minimizing pathway. It assumes 

that all nations of the world undertake emissions mitigation simultaneously 

and effectively, and share a common global price that all emissions to the 

atmosphere must pay with emissions of different gases priced according to 

their hundred-year global warming potentials (Forster et al., 2007). All 

sectors of the economy are covered, including agriculture and land use 

emissions. That emissions price also rises over time so as to minimize the 

present discounted cost of emissions mitigation. The policy also assumes 

that deployment mechanisms and measurement and monitoring of both 

fossil fuel and terrestrial carbon are not barriers to implementation of 

emissions mitigation.

This cost-minimizing price path has two components. Prior to reaching the 

target, 4.5 W m-2, cost minimization requires that the greenhouse gas 

emissions price rise at the interest rate, adjusted by the rate of ocean uptake 

(Edmonds et al., 2008; Clarke et al., 2007; Hotelling, 1931; Peck and Wan, 

1996). An emissions price path with this property precludes all 

opportunities for arbitrage because the marginal cost of abatement is 

constant across time. The second component of the pathway occurs after the 

target is reached. At this time, the emissions price is adjusted to ensure that 
6

the radiative forcing level remains at its target. For the RCP4.5, stabilization 

occurs in 2080; prior to 2080 the emissions price rises at 5% per year, and 

after 2080 the emissions price is roughly constant.

2.2 Emissions Downscaling 

Emissions from GCAM were downscaled using a two-step method, first 

downscaling to the country level and then mapping to a spatial grid within 

each country. Detailed emissions from GCAM were aggregated into the 12 

RCP reporting sectors for the 14 GCAM regions at each 15-year model time 

period. Emissions from each sector were downscaled to a country level for 

231 countries using the methodology outlined in Van Vuuren et al. (2007). 

Input data for this step includes the country-level population projection used 

for the RCP4.5 scenario, a gridded base-year GDP data set from van Vuuren et 

al. (2007), who combined World Bank GDP information with the GPW 

gridded population data set (CIESIN & CIAT 2005), and year 2000 gridded 

emissions data from Lamarque et al. (2010). Gridded GDP and emissions data 

were used so that base-year GDP and emissions differences could 

consistently be estimated for any set of countries or regions. A convergence 

year of 2200 for GDP and emissions intensity calculations (slightly larger 

than value used by Van Vuuren et al. 2007) was used for all anthropogenic 

emissions sectors. The pattern of forest and grassland emissions within each 

region was held constant by setting a high convergence year of 10,000. 

The downscaled sectoral emissions for each country were mapped to a 0.5 

degree grid using the base-year 2000 gridded emissions data from Lamarque 

et al. (2010). The relative emissions distribution within each country was 

held constant over time for each emissions sector. All downscaling 

calculations were performed with each 0.5 degree grid cell subdivided into 

231 countries using 2.5 minute GPW country boundary data (CIESIN & CIAT 

2005). After downscaling on a sub-divided grid for each country and 

 

1 Note that the final concentration pathway values for the RCP4.5 were produced in MAGICC 

version 6 (see Meinhausen et al., this issue).
7

emissions sector, emissions were summed to a 0.5 degree resolution for the 

final data product. 

Emissions from international shipping and aircraft do not occur within 

country boundaries and instead were aggregated to one global emissions 

figure. Gridded shipping emissions were globally scaled from the RCP 

consensus year 2000 emissions grid (Lamarque et al. 2010). Aircraft 

emissions used a time changing pattern from the QUANTIFY B2i emissions 

scenario (Lee et al. 2010), as the overall pathway for this scenario closely 

matched the GCAM model output. The QUANTIFY three dimensional 

emissions pattern was collapsed to two dimensions (latitude and longitude) 

for 2000, 2025, 2050, and 2100. This pattern was interpolated to decadal 

intervals and scaled globally to match the GCAM global aviation emissions 

values. 

2.3 Land Use Downscaling

The RCP scenario process is the first to explicitly provide land use projections 

in addition to future emissions pathways for input to global climate models. 

Because all four participating integrated assessment models, and all receiving 

climate models, use different characterizations and definitions of land use 

types and transitions, a harmonization step was necessary. The 

harmonization was designed to provide a continuous, consistent set of land 

use inputs for climate models from 1500 through 2100 with a smooth 

transition between historical data (1500-2005) and future projections 

(2005-2100) (see Hurtt et al., this volume). 

In the GCAM model results, land use is simulated at the 14 region level and 

land use changes and transitions are not spatially attributed. In this case, the 

land use was first downscaled to the 0.5 degree harmonization grid, following 

the algorithms of the the global land-use model (GLM) (Hurtt et al. 2006), 

preserving GCAM regional land use area totals and generating smooth spatial 

patterns in the transition from historical to future states. These downscaling 

algorithms were developed and implemented by the land use harmonization 
8

team at the University of New Hampshire (Hurtt et al., this volume) and are 

fully described in Thomson et al. (2010). 

3. RESULTS

3.1 GCAM Reference Scenario

Each of the RCPs was produced by a different integrated assessment model; 

therefore, each has its own reference scenario. Thus, the reference scenario 

for RCP 4.5 is not RCP8.5 but rather a GCAM reference scenario. The GCAM 

reference scenario (Clarke et al., 2007) depicts a world in which global 

population reaches a maximum of more than 9 billion in 2065 and then 

declines to 8.7 billion in 2100 while global GDP grows by an order of 

magnitude and global energy consumption triples. The reference scenario 

includes no explicit policies to limit carbon emissions, and therefore fossil 

fuels continue to dominate global energy consumption, despite substantial 

growth in nuclear and renewable energy. Atmospheric CO2 concentrations 

rise throughout the century and reach 792 ppmv by 2100, with total 

radiative forcing approaching 7 W m2 (Fig. 1). Forest land declines in the 

reference scenario to accommodate increases in land use for food and 

bioenergy crops. Even with the assumed agricultural productivity increases, 

crop land increases in the first half of the century due to increases in

population and income, which drives an increase in land-intensive meat 

consumption. After 2050 the rate of growth in food demand slows, in part 

due to declining population. As a result the amount of cropland and also land 

use change (LUC) emissions decline as agricultural crop productivity 

continues to increase. 

3.2 4.5 Stabilization Scenario 

The RCP4.5 scenario is based on the same population and income drivers as 

the GCAM reference scenario but applies greenhouse gas emissions valuation 

policies to stabilize atmospheric radiative forcing at 4.5 W m-2 in 2100 (Fig. 

1). This imperative to stabilize climate change drives anthropogenic CO2

emissions downward throughout the next century (Fig. 2). RCP4.5 results in 
9

an atmospheric CO2 concentration of 526 ppm in 21002, compared to 792 

ppm in the GCAM reference case. This stabilization is achieved in 2080. At 

this point in time, total radiative forcing reaches 4.5 W m-2 and the emissions 

price becomes roughly constant. CO2 emissions also become roughly 

constant. RCP4.5 depicts declines in overall energy use, as well as declines in 

fossil fuel use compared to the reference case, while substantial increases in 

renewable energy forms and nuclear energy both occur (Fig. 3). The 

proportion of total final energy that is supplied by electricity also increases 

due to fuel switching in the end-use sectors. The emergence of large-scale 

carbon dioxide capture and storage (CCS) (Fig. 4) allows continued use of 

fossil fuels for electricity generation and cement manufacture, among other 

uses, though total use is lower than in the reference scenario. Bioenergy with 

CCS is used to produce electricity, providing an energy source that is carbonnegative with respect to the atmosphere. The amount of bioenergy deployed 

is limited by the availability of dedicated crop and crop residue feedstocks 

from the land system. 

One important feature influencing the availability of bioenergy feedstocks in 

the RCP4.5 is the expansion of forests as part of the larger emissions 

mitigation strategy. The extent of afforestation follows Wise et al., 2009b. 

This idealized case assumes that all carbon from fossil fuel and land use 

emissions are charged an equal penalty price, and thus reductions in LUC 

emissions constitute an available strategy for global emissions mitigation. 

The GCAM therefore simulates the preservation of large stocks of terrestrial 

carbon in forests, with some crop and pasture lands converted to bioenergy 

crops (Fig. 5). Under this policy environment, bioenergy crops still provide 

an important source of fuel, >50 EJ/yr, to meet global energy demand in 

2100. This is accomplished while still providing for the world’s dietary need 

by shifting toward food products with a smaller carbon footprint.

 

2

526 ppmv is the CO2 concentration from GCAM before harmonization in MAGICC6 (see 

Meinhausen et al., this issue. The harmonized RCP4.5 CO2 concentration in 2100 is 538 ppmv.
10

Carbon prices reach $85 per ton of CO2 by 2100 (Fig. 6) which transforms the 

global economy. Electric power generation changes from the largest source 

of emissions in the world to a system with net negative emissions—made 

possible by increased reliance on nuclear and renewable energy forms such 

as wind, solar and geothermal, and the application of CO2 capture and storage 

technology to both fossil fuel sources and bioenergy (Figs. 3 and 4). 

Buildings and industry largely de-carbonize by employing more efficient enduse technologies and by electrifying. Annual land-use change emissions are 

reduced to 0.13 GtCO2/yr (Fig. 2). Total anthropogenic CO2 emissions for the 

RCP4.5 peak around 42 Gt CO2 per year (Fig. 2) around 2040 and decline to 

2080 before leveling off around 15 Gt CO2 per year for the remainder of the 

century. Other greenhouse gases respond to both the mitigation price 

signals in the GCAM as well as to assumed pollution controls. Downscaling of 

these emissions leads to additional insights about future non-CO2 emissions 

that are important considerations in the global climate and atmospheric 

chemistry models. For example, aggregate emissions and the associated 

radiative forcing contribution of CH4 from all sectors are relatively constant 

at the global level (Fig. 7); however, when downscaled they exhibit 

geographical shifts (Fig. 8). CH4 emissions in South America and Africa 

increase over the century while those from China, India the US and Western 

Europe decline. 

CO2 constitutes the largest contribution to total radiative forcing in the 

RCP4.5, followed by CH4, halocarbons, tropospheric ozone, and N2O (Fig. 7). 

The relative proportion of the non-CO2 components of positive radiative 

forcing remains constant over time. Sulfate forcing is net negative throughout 

the century but this influence declines over time largely due to assumed 

increases in pollution control with income, although there are also indirect 

sulfur dioxide emissions reductions due to the greenhouse gas mitigation 

policy (Smith et al. 2005). 
11

3.3 GCAM-Simulation of the Four Pathways

In order to facilitate model intercomparisons and further explore the 

characteristics of the RCPs, the participating models simulated their assigned 

RCP as well as the other three defined radiative forcing levels. The GCAM 

was used to simulate a 2.6 W m-2 peak-and-decline scenario for use in the 

evaluation of low radiative forcing targets during the planning stages of the 

RCPs (Weyant et al, 2009) and is fully documented in Calvin et al (2009). The 

GCAM6.0 was simulated as a stabilization following the same methods as the 

GCAM4.5 but resulting in lower carbon prices and a longer time to 

stabilization. All three of the mitigation cases with GCAM (2.6, 4.5 and 6.0 W 

m-2) used the same technology, population and economic assumptions 

described earlier in this paper and in Clarke et al. (2007). The GCAM 

reference case with these assumptions and no climate mitigation policy 

reaches around 7.0 W m-2 radiative forcing in 2100. Thus, to reach the RCP 

level of 8.5 W m2 required altering some underlying assumptions. Several 

modifications of underlying assumptions were tested; the case selected for 

the GCAM8.5 follows the same population and economic drivers as the other 

GCAM scenarios, but assumes no technological improvement in energy 

technologies or agricultural productivity. In other words, the GCAM8.5 is the 

GCAM reference case if all technological development is frozen after 2005. 

This is a hypothetical experiment in exploring high levels of radiative forcing 

which also allows exploration of the role of technological development in 

scenarios. 

The CO2 emissions from the four pathways simulated with GCAM are 

illustrated in Fig. 9 along with the four official released RCPs. The GCAM2.6 

results in even lower emissions of CO2 than the RCP2.6. Total radiative 

forcing still declines to 2.6 W m-2 as a result of higher CH4 and N2O emissions 

in GCAM than in the IMAGE for this scenario. Conversely, CO2 emissions for 

the GCAM8.5 are higher than the RCP8.5 due, but the same radiative forcing 

is reached due to lower CH4 and N2O emissions in the GCAM than in the 

MESSAGE model for this scenario. 
12

Differences in emissions by gas between the official RCPs and the GCAM 

replication of the RCP forcing levels can be attributed to any number of 

forces. First, GCAM employs different population and GDP assumptions than 

the other three models. GCAM has the smallest population and the second 

highest GDP of the four models (see van Vuuren et al., this issue). Second, the 

four models have different assumptions about technological change and 

resource availability. Third, the GCAM model uses a terrestrial carbon policy 

that has a significant impact on land use and land-use change emissions. 

While each of the models consider abatement opportunities in the terrestrial 

system, the method of attaining these opportunities differs across the four 

RCP models. The differences listed here are only a subset of differences 

between the four models. However, they illustrate an important point; 

namely, there are numerous ways that a given radiative forcing goal can be 

achieved. The RCP4.5 is only one pathway to stabilize radiative forcing at 4.5 

W/m2.

4. CONCLUSIONS

The RCP4.5 scenario is intended to inform research on the atmospheric 

consequences of reducing greenhouse gas emissions in order to stabilize 

radiative forcing in 2100. It is also a mitigation scenario – the 

transformations in the energy system, land use, and the global economy 

required to achieve this target are not possible without explicit action to 

mitigate greenhouse gas emissions. However, there are many possible 

pathways in GCAM and other integrated assessment models that would also 

achieve a radiative forcing level of 4.5 Wm-2. For example, simulations with 

GCAM can reach 4.5 Wm-2 even if some technology options, such as CCS or 

nuclear power, are removed from consideration or even if not all countries 

enter into an emissions mitigation agreement at the same time (Clarke et al., 

2009). Such alternate scenarios have different characteristics – higher 

emissions prices and different energy system transformations, for example – 

than the RCP4.5. The pathway discussed here and released as RCP4.5 is costminimizing, and therefore invokes all available technology options that can 

cost-effectively contribute to mitigation. 
13

RCP4.5 aims to achieve stable radiative forcing in 2100; however, this does 

not imply that greenhouse gas emissions, greenhouse gas concentrations, or 

the climate system are stable. Radiative forcing is stable from 2080-2100 in 

the RCP4.5, but emissions and concentrations of greenhouse gases continue 

to vary in the underlying scenario. As a separate exercise, the greenhouse 

gas emissions and concentrations of RCP4.5 were extended to 2300 using 

MAGICC 6 (Meinhausen et al., this volume). This ECP4.5 is also defined as a 

stabilization path, and therefore radiative forcing is held constant at 4.5 W m2 from 2100-2300. It is important to note that ECP4.5 does not imply an 

extension of the socioeconomic, energy or land use assumptions underlying 

RCP4.5 in GCAM. The application of RCP4.5 and ECP4.5 in climate models 

provides a platform to explore the climate system response to stabilizing the 

anthropogenic components of radiative forcing. 

Acknowledgements: Funding was provided by the US Department of Energy, Office of Science 

through the Integrated Assessment Research Program. The authors wish to thank the many 

scientists and collaborators involved in the planning and development of the RCP process, and 

especially the AIM, MESSAGE and IMAGE modeling teams for time devoted to scenario review 

and coordination. 
14

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Implications of Limiting CO2 Concentrations for Agriculture, Land-use Change Emissions, 

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Wise M, Calvin K, Thomson A, Clarke L, Sands R, Smith SJ, Janetos A, Edmonds J (2009b) 

Implications of Limiting CO2 Concentrations for Land Use and Energy. Science 324:1183-

1186
16

0

2

4

6

8

2005 2020 2035 2050 2065 2080 2095

Year

W /m2

Reference

RCP4.5

Figure 1: Radiative forcing ( W m-2) of the GCAM reference and RCP4.5 scenarios over the model 

simulation period
17

0

5

10

15

20

2005 2020 2035 2050 2065 2080 2095

Year

C O2 Emissions (GtC/yr)

Reference - Energy/Industrial

RCP4.5 Energy/Industrial

Reference - Land Use

RCP4.5 - Land Use

Figure 2: CO2 emissions from energy and industrial sources and from land use/ land use change in 

the GCAM reference and RCP4.5 scenarios
18

-500

-400

-300

-200

-100

0

100

200

300

400

500

2005 2020 2035 2050 2065 2080 2095

Year

EJ/yr

energy reduction

other

hydro

biomass

nuclear

coal

gas

oil

Figure 3: Primary energy sources in RCP4.5 expressed as difference from the reference case. 

Categories above the x-axis indicate a greater amount of primary energy from that source in the 

RCP4.5 whereas values below indicate less energy from that primary source in the RCP4.5. 
19

-250

-200

-150

-100

-50

0

50

100

150

200

250

2005 2020 2035 2050 2065 2080 2095

Year

EJ/yr

energy reduction

other

hydro

nuclear

biomass w/ccs

biomass

coal w/ccs

coal

gas w/ccs

gas

oil w/ccs

oil

Figure 4: Electricity generation technology in RCP4.5 expressed as difference from the reference 

case. Categories above the x-axis indicate a greater amount of electricity generation from that 

technology in the RCP4.5 whereas values below indicate less electricity generation from that 

technology in the RCP4.5.
20

Figure 5: Global land cover over time in the RCP4.5 scenario expressed as a percentage of total 

global land area.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2005 2020 2035 2050 2065 2080 2095

Year

Percent of all land

Rock/Ice/Desert

Tundra

Forest

Pasture

Grassland/Shrubland Biomass

Crops
21

0

15

30

45

60

75

90

2005 2020 2035 2050 2065 2080 2095

Year

2005$/tCO2

Reference

RCP4.5

Figure 6: Price of CO2 per ton (2005$) in the RCP4.5 scenario over the simulation period. 
22

-2

-1

0

1

2

3

4

5

6

2005 2020 2035 2050 2065 2080 2095

Year

W /m2

CO2 CH4 N2O Halocarbons Tropospheric Ozone Sulfur (Direct & Indirect) Other

Figure 7: Contributions of the different greenhouse gases to total radiative forcing in the RCP4.5 

scenario.
23
24

Figure 8: Global CH4 emissions (in Tg per grid cell per year) downscaled from the GCAM RCP4.5 

scenario for 2005, 2050 and 2100. 
25

-20

0

20

40

60

80

100

120

140

160

2005 2020 2035 2050 2065 2080 2095

Year GtCO2/yr

GCAM8.5 RCP8.5

GCAM6.0 RCP6.0

RCP4.5 GCAM2.6

RCP2.6

Figure 9: Annual CO2 emissions (GtCO2) from all anthropogenic sources for the four released RCPs 

(RCP2.6, RCP4.5, RCP6.0, RCP8.5) and the corresponding pathways simulated with the GCAM 

model (GCAM2.6, GCAM6.0, GCAM8.5).