Energy demand

Baseline energy service demands are provided exogenously to MESSAGEix, though they can be adjusted endogenously based on energy prices using the MESSAGEix-MACRO link. There are seven energy service demands that are provided to MESSAGEix, including:

1. Residential/commercial thermal

2. Residential/commercial specific

3. Industrial thermal

4. Industrial specific

5. Industrial feedstock (non-energy)

6. Transportation

7. Non-commercial biomass.

These demands are generated using a so-called scenario generator which is implemented in the script language R. The scenario generator relates historical country-level GDP per capita (PPP) to final energy and, using projections of GDP (PPP) and population, extrapolate the seven energy service demands into the future. The sources for the historical and projected datasets are the following:

1. Historical GDP (PPP) – World Bank (World Development Indicators, 2012 [119])

2. Historical Population – UN Population Division (World Population Projection, 2010 [10])

3. Historical Final Energy – International Energy Agency Energy Balances (IEA, 2012 [1])

4. Projected GDP (PPP) – Dellink et al. (2015) [9], also see Shared Socio-Economic Pathways database (SSP scenarios)

5. Projected Population – KC and Lutz (2014) [40], also see Shared Socio-Economic Pathways database (SSP scenarios)

The scenario generator runs regressions on the historical datasets to establish the relationship for each of the eleven MESSAGEix regions between the independent variable (GDP (PPP) per capita) and the following dependent variables:

1. Total final energy intensity (MJ/2005USD)

2. Shares of final energy among several energy end-use sectors (transport, residential/commercial and industry)

3. Shares of electricity use between the industrial and residential/commercial sectors.

In the case of final energy intensity, the relationship is best modeled by a power function so both variables are log-transformed. In the case of most sectoral shares, only the independent variable is log-transformed. The exception is the industrial share of final energy, which uses a hump-shaped function inspired by Schafer (2005) [100].

In parallel, the same historical data are used, now globally, in quantile regressions to develop global trend lines that represent each percentile of the cumulative distribution function (CDF) of each dependent variable. Given the regional regressions and global trend lines, final energy intensity and sectoral shares can be extrapolated based on projected GDP per capita, or average income.

A basic assumption here is that the regional trends derived above will converge to certain quantiles of the global trend when each region reaches a certain income level. Hence, two key user-defined inputs allow users to tailor the extrapolations to individual socio-economic scenarios: convergence quantile and the corresponding income. In the case of final energy intensity (FEI), the extrapolation is produced for each region by defining the quantile at which FEI converges (e.g., the 20th percentile within the global trend) and the income at which the convergence occurs. For example, while final energy intensity converges quickly to the lowest quantile (0.001) in SSP1, it converges more slowly to a larger quantile (0.5 to 0.7 depending on the region) in SSP3. Convergence quantiles and incomes are provided for each SSP and region in Table 21, Table 22, Table 23. The convergence quantile allows one to identify the magnitude of FEI while the convergence income establishes the rate at which the quantile is approached. For the sectoral shares, users can specify the global quantile at which the extrapolation should converge, the income at which the extrapolation diverges from the regional regression line and turns parallel to the specified convergence quantile (i.e., how long the sectoral share follows the historical trajectory), and the income at which the extrapolation converges to the quantile. Given these input parameters, users can extrapolate both FEI and sectoral shares.

The total final energy in each region is then calculated by multiplying the extrapolated final energy intensity by the projected GDP (PPP) in each time period. Next, the extrapolated shares are multiplied by the total final energy to identify final energy demand for each of the seven energy service demands used in MESSAGE. Finally, final energy is converted to useful energy in each region by using the average final-to-useful energy efficiencies used in the MESSAGE model for each model region (Regions).

Table 21 Convergence quantile and income for each quantity and region for SSP1 (for region descriptions, see: Regions)

SSP1	AFR	CPA	EEU	FSU	LAM	MEA	NAM	PAO	PAS	SAS	WEU
Convergence Quantile
Final Energy Intensity (FEI)	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001	0.001
Share NC Biomass	0.01	0.25	0.01	0.75	0.01	0.3	0.01	0.01	0.01	0.01	0.01
Share Transport	0.05	0.02	0.2	0.05	0.2	0.05	0.2	0.2	0.04	0.03	0.2
Share Res/Com	0.25	0.25	0.2	0.2	0.28	0.3	0.25	0.2	0.28	0.3	0.2
Share Industry	0.1	0.2	0.1	0.5	0.28	0.2	0.3	0.3	0.28	0.2	0.3
Elec Share Res/Com	0.45	0.45	0.45	0.45	0.63	0.62	0.4	0.63	0.62	0.64	0.43
Feedstock Share Industry	0.18	0.2	0.24	0.24	0.2	0.26	0.26	0.23	0.26	0.22	0.24
Elec Share Industry	0.4	0.4	0.42	0.36	0.4	0.33	0.36	0.36	0.4	0.4	0.4
Convergence Income
Final Energy Intensity (FEI)	112295	98603	299177	112307	100188	113404	112356	112261	106323	112300	107636
Share NC Biomass	5981	46015	34405	40951	20038	34894	112356	112261	16357	11105	48153
Share Transport	99676	32868	112341	71664	112310	113404	123018	94337	112293	97169	141627
Share Res/Com	119611	112276	179506	153565	112310	112270	123018	157229	112293	112300	141627
Share Industry	39870	105177	164547	92139	40075	112270	123018	112261	126769	83288	127464
Elec Share Res/Com	112295	112276	112341	112307	112310	87234	131219	132072	112293	112300	112168
Feedstock Share Industry	112295	112276	112341	112307	112310	112270	123018	125783	112293	112300	112168
Elec Share Industry	112295	98603	299177	112307	100188	113404	112356	112261	106323	112300	107636

Table 22 Convergence quantile and income for each quantity and region for SSP2 (for region descriptions, see: Regions)

SSP2	AFR	CPA	EEU	FSU	LAM	MEA	NAM	PAO	PAS	SAS	WEU
Convergence Quantile
Final Energy Intensity (FEI)	0.03	0.03	0.03	0.04	0.04	0.04	0.05	0.02	0.03	0.03	0.02
Share NC Biomass	0.6	0.6	0.75	0.75	0.25	0.75	0.75	0.75	0.6	0.6	0.75
Share Transport	0.05	0.04	0.15	0.1	0.5	0.3	0.5	0.14	0.2	0.05	0.15
Share Res/Com	0.15	0.28	0.5	0.5	0.3	0.5	0.3	0.35	0.3	0.28	0.33
Share Industry	0.25	0.4	0.15	0.25	0.15	0.25	0.25	0.25	0.25	0.6	0.25
Elec Share Res/Com	0.42	0.4	0.35	0.22	0.58	0.6	0.14	0.57	0.6	0.51	0.18
Feedstock Share Industry	0.15	0.22	0.26	0.26	0.18	0.27	0.32	0.27	0.3	0.22	0.27
Elec Share Industry	0.39	0.38	0.4	0.45	0.35	0.4	0.4	0.4	0.4	0.43	0.35
Convergence Income
Final Energy Intensity (FEI)	200009	200033	299177	266179	199975	139574	246036	141506	199968	200002	199977
Share NC Biomass	19935	26294	77786	40951	20038	94649	94724	132072	12268	18046	48153
Share Transport	49838	105177	94540	94596	80150	94649	94724	94652	81787	27763	99139
Share Res/Com	119611	65735	89753	71664	94577	69787	94724	110060	81787	83288	113301
Share Industry	31896	105177	44877	102377	100188	78511	94724	141506	98144	13881	94607
Elec Share Res/Com	69773	94593	94540	102377	94577	87234	123018	141506	94627	55525	113301
Feedstock Share Industry	19935	94593	94540	94596	94577	94649	94724	94652	94627	94615	94607
Elec Share Industry	200009	200033	299177	266179	199975	139574	246036	141506	199968	200002	199977

Table 23 Convergence quantile and income for each quantity and region for SSP3 (for region descriptions, see: Regions)

SSP3	AFR	CPA	EEU	FSU	LAM	MEA	NAM	PAO	PAS	SAS	WEU
Convergence Quantile
Final Energy Intensity (FEI)	0.6	0.55	0.5	0.7	0.7	0.5	0.7	0.5	0.5	0.7	0.6
Share NC Biomass	0.9	0.6	0.75	0.75	0.25	0.75	0.75	0.75	0.6	0.9	0.75
Share Transport	0.1	0.05	0.7	0.2	0.45	0.5	0.7	0.25	0.5	0.1	0.7
Share Res/Com	0.25	0.25	0.55	0.55	0.3	0.5	0.35	0.6	0.25	0.2	0.5
Share Industry	0.1	0.6	0.2	0.1	0.2	0.2	0.1	0.1	0.6	0.2	0.1
Elec Share Res/Com	0.4	0.6	0.45	0.4	0.9	0.9	0.25	0.65	0.9	0.6	0.33
Feedstock Share Industry	0.2	0.22	0.26	0.24	0.2	0.3	0.32	0.29	0.3	0.22	0.27
Elec Share Industry	0.3	0.43	0.37	0.45	0.3	0.4	0.35	0.45	0.4	0.35	0.4
Convergence Income
Final Energy Intensity (FEI)	200009	200033	200000	200044	199975	200027	200109	199995	199968	200002	199977
Share NC Biomass	13955	26294	80927	40951	12023	80953	80782	132072	12268	12771	48153
Share Transport	13955	46015	59835	51188	70131	69787	80782	132072	32715	55525	81010
Share Res/Com	23922	65735	59835	61426	80952	52340	80782	80816	199968	80512	81010
Share Industry	5981	52588	200000	122852	18034	43617	200109	199995	81787	30539	198277
Elec Share Res/Com	80976	80986	80927	61426	80952	69787	80782	80816	80969	80956	81010
Feedstock Share Industry	19935	26294	80927	80980	80952	80953	80782	80816	80969	80956	81010
Elec Share Industry	200009	200033	200000	200044	199975	200027	200109	199995	199968	200002	199977