TRACKING SDG 7

THE ENERGYPROGRESSREPORT

2020

A joint report of the custodian agencies
United Nations
Statistics Division© 2020 International Bank for Reconstruction and Development / The World Bank
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Report designed by: Duina Reyes
Cover photo: Vincent Tremeau/World BankTRACKING SDG 7

THE ENERGYPROGRESSREPORT

2020

A joint report of the custodian agencies
United Nations
Statistics Division

PARTNERS
The development of the Energy Progress Report was made possible by the exceptional collaboration between the five
SDG 7 custodian agencies, specially constituted in a Steering Group:International Energy Agency (IEA)

World Bank (WB)International Renewable Energy Agency (IRENA)

World Health Organization (WHO)

United Nations Statistics Division (UNSD)

The Steering Group was supported by a Technical Advisory Group composed as follows:

African Development Bank (AfDB)

UAE (Ministry of Foreign Affairs)



Clean Cooking Alliance

United Nations Association of China

Denmark (Ministry of Foreign Affairs)

United Nations Children's Fund (UNICEF)

ENERGIA

European Commission

United Nations Department of Economics and Social
Affairs (UN DESA)FIA Foundation



United Nations Development Programme (UNDP)

Food and Agricultural Organization (FAO)Germany (Federal Ministry for Economic Cooperation
and Development)

United Nations Economic Commission for Africa(UNECA)





Hivos

United Nations Economic Commission for Asia andthe Pacific (ESCAP)International Institute for Applied Systems Analysis



United Nations Economic Commission for Latin
America and the Caribbean (ECLAC)

International Labour Organization (ILO)

Islamic Development Bank

United Nations Economic Commission for Western
Asia (ESCWA)Kenya (Ministry of Energy & Petroleum)

Latin American Energy Organization (OLADE)

United Nations Economic Programme for Europe(UNECE)

Norway (Ministry of Foreign Affairs)

United Nations Environment Programme (UNEP)

Pakistan (Ministry of Foreign Affairs)

Renewable Energy Policy Network for the 21ST
Century (REN 21)

United Nations Framework Convention on Climate
Change (UNFCCC)

Sustainable Energy for All (SEforALL)

TERI School of Advanced Studies



The Netherlands (Ministry of Foreign Affairs)

United Nations Human Settlements Programme(UN-Habitat)

United Nations Industrial Development Organization(UNIDO)The United Nations Office of the High Representative
for the Least Developed Countries, Landlocked 
Developing Countries and Small Island Developing
States (UN -OHRLLS)

United Nations Institute for Training and Research(UNITAR)
Vienna University of Technology

The Steering Group's work for the 2020 edition of the report was chaired by IRENA and made possible by agreement
among the senior management of the member agencies. Fatih Birol (IEA), Francesco La Camera (IRENA), Stefan
Schweinfest (UNSD), Riccardo Puliti (World Bank), and Maria Neira (WHO) with Rohit Khanna (ESMAP) oversaw
the development of the Energy Progress Report in collaboration with Minoru Takada (UNDESA). The technical coleadership of the project by the custodian agencies was the responsibility of Laura Cozzi (IEA), Rabia Ferroukhi(IRENA), Leonardo Souza (UNSD), Elisa Portale (World Bank), and Heather Adair-Rohani (World Health Organization).
Financial support from ESMAP is gratefully acknowledged.

CONTENTS

Executive Summary............................................................................................... iv

CHAPTER 1: Access to Electricity....................................................................... 14

CHAPTER 2: Access to Clean Fuels and Technologies for Cooking................. 42

CHAPTER 3: Renewable Energy......................................................................... 70

CHAPTER 4: Energy Efficiency........................................................................... 92

CHAPTER 5: Outlook for SDG 7......................................................................... 118
CHAPTER 6: Tracking SDG 7 Progress Across Targets:
Indicators and Data.............................................................................................144
Acknowledgments ..............................................................................................194

Abbreviations and Acronyms.............................................................................. 197

iii

Photo: Shutterstock

Photo: World BankEXECUTIVE SUMMARYEXECUTIVE
SUMMARY

T

he 2020 edition of Tracking SDG 7: The Energy Progress Report monitors and assesses attainments in the global
quest for universal access to affordable, reliable, sustainable, and modern energy by 2030. The latest available
data and select energy scenarios are set forth in this year’s report, which finds that although the world continues
to advance toward SDG 7, its efforts fall well short of the scale required to reach the goal by 2030.
The data and analyses presented in these pages were prepared before the covid-19 pandemic and must be viewed
in the light of this unprecedented crisis. Like most grave crises, the covid-19 pandemic shows how an unforeseen
global calamity can disrupt trends and policies of long standing, with outcomes both expected and unpredictable, direand surprising. With its widespread impact on societies and economies at all levels, including plummeting oil prices,
disrupted supply chains, and the limited ability of many households and businesses to pay for electricity services, thepandemic is certain to affect the energy transition and progress toward SDG 7. At the same time, the crisis is pointing
to the urgent need for access to reliable, affordable, sustainable, and modern energy—for hospitals and health facilities
to treat patients, for schools to prepare children for the digital economy, for communities to pump clean water, andfor people to gain access to information. The full impact of the covid-19 pandemic on energy access, energy efficiency,
renewable energy deployment, and the full energy transition remains to be seen.
In response to the pandemic, countries around the world will have to take exceptional measures to bring the healthemergency under control, limit its human toll, and avoid deep recession. Under such circumstances, countries havean opportunity to consider options for economic stimulus that not only respond to the immediate crisis, but also
ensure longer-term social, economic, and environmental sustainability. At the heart of such objectives is access tomodern energy, with its immense potential to spur the achievement also of other Sustainable Development Goals andglobal climate objectives. The SDG 7 custodian agencies—the International Energy Agency (IEA), the International
Renewable Energy Agency (IRENA), the United Nations Statistics Division (UNSD), the World Bank, and the World
Health Organization (WHO)—therefore urge the international community and policy-makers to safeguard the gains
already attained for SDG 7 and not lose sight of the need to continue action on affordable, reliable, sustainable, andmodern energy for all.
According to the custodian agencies, the latest data on progress toward SDG 7, before the onset of the pandemic,
demonstrated that stepped-up efforts toward all targets were urgently required if SDG 7 was to be met within the
coming decade. Even greater efforts will be needed to meet the SDG 7 targets in a post covid-19 world.
Universal access. SDG target 7.1 is universal access to affordable, reliable, sustainable, and modern energy services;with 7.1.1 focusing on access to electricity and 7.1.2 focusing on access to clean cooking solutions. Recent years haveseen rapid growth in access to electricity after an accelerated deployment of affordable electrification options, including
on- and off-grid solutions. As a result, the global population lacking access to electricity dropped to 789 million in 2018,from 1.2 billion in 2010 (Figure ES.1). By contrast, the global population without access to clean cooking solutions
remained largely unchanged during the same period, standing at close to 3 billion. The rate of increase in access toclean cooking has even decelerated since 2012, falling behind population growth in some countries. Increased efforts
are needed to ensure universal access to both electricity and clean cooking, consistent with SDG target 7.1.
Renewable energy. Target 7.2 aims to increase substantially the share of renewable energy in the global energy mix.
That share continued to increase in 2017 (+ 0.1 percentage points), although at a slower pace than the year before (+0.2 percentage points), reaching 17.3 percent of total final energy consumption (TFEC) in 2017, up from 17.2 percent in2016 and 16.3 percent in 2010. Solar PV and wind are key drivers behind the fast-growing share of renewables in thegeneration of electricity. But renewables’ share in the heating and transportation sectors lags far behind its potential.
An acceleration of renewables in all sectors will be needed to achieve target 7.2.

1

FIGURE ES.1 • Latest data on primary indicators of global progress toward SDG 7 targets

2010

Latest year

people without
access to electricity

people without
access to electricity

3billion

2.8
billion

1.2
billion(2018)

people without
access to clean cooking

people without
access to clean cooking

16.3%

17.3%

(2018)

share of total final
energy consumption
from renewables

share of total final
energy consumption
from renewables

5.9
MJ/USD

5.0
MJ/USD(2017)

primary energy
intensity

primary energy
intensity

10.1
USD billion

21.4
USD billion

international financial
flows to developing
countries in supportof clean energy

2789
million(2017)

international financial
flows to developing
countries in supportof clean energy(2017)

Tracking SDG 7: The Energy Progress Report 2020

Energy efficiency. SDG target 7.3 is to double the global rate of improvement in energy efficiency by 2030, over thetrend observed between 1990 and 2010, which was 1.3 percent. Global primary energy intensity, defined as total
primary energy supply per unit of GDP, reached 5.0 megajoules per USD dollar in 2017, equivalent to a 1.7 percent rateof improvement from 2016—the lowest since 2010. Preliminary estimates for 2018 (1.3 percent) and 2019 (2 percent)suggest that the improvement rate would reach approximately 2.1 percent between 2010-2019 which is lower than therequired 2.6 percent annual target rate for the years between 2010 and 2030. Consequently, achieving the goal will
require an energy intensity improvement rate of at least 3 percent per year from now through to 2030—a challenging
proposition.
International public finance. Finally, target 7.A is to promote access to technology and investments in clean energy,
with 7.A.1 focusing on international public financial flows to developing countries in support of clean and renewableenergy. Total flows reached USD 21.4 billion in 2017, double the level of 2010. Although this is a promising increase, only
12 percent of financial flows in 2017 reached the least-developed countries, which are the furthest from achieving thevarious SDG 7 targets. Increased efforts are needed to make sure finance reaches the countries most in need.
***In addition to reviewing progress toward SDG 7 targets, this report identifies best practices, policies, and measuresto accelerate progress while supporting the achievement of other SDGs. The chapters that follow include boxes
that identify the linkages between SDG 7 and other SDGs. The report also describes the results of global modelingexercises conducted by IEA and IRENA to determine whether current—which is to say, pre-covid-19—policy ambitions
are sufficient to meet the SDG 7 targets and, if they are not, what additional actions are needed for success. The final
chapter of the report contains an overview of indicators and suggests ways to further improve the underlying data andthe tracking of advances.

Executive Summary3

ACCESS TO ELECTRICITY

T

he share of the global population with access to electricity increased from 83 percent in 2010 to 90 percent in
2018, enabling more than a billion people to gain access during the period. The population still without access toelectricity was 789 million in 2018, down from 1.2 billion in 2010.

The global advance of electrification accelerated slightly in recent years, rising from an average of 0.77 percentage
points annually between 2010 and 2016 (127 million people/year) to 0.82 percentage points between 2016 and 2018(136 million people/year). These numbers nevertheless fall short of the gains needed to achieve the goal of universal
access to electricity by 2030. Annual increases of at least 0.87 percentage points would be required to meet the target.
Under current and planned policies before the start of the COVID-19 crisis, it is estimated that about 620 million people
will remain without access in 2030, 85 percent of them in Sub-Saharan Africa.
The global advance in access to electricity since 2010 masks unequal progress across regions (Figure ES.2). Latin
America and the Caribbean and Eastern Asia and South-eastern Asia approached universal access, exceeding
98 percent access to electricity by 2018. In Central Asia and Southern Asia, more than 92 percent of the population
had gained access to electricity by 2018. The world’s access deficit is increasingly concentrated in Sub-Saharan Africa,
where the access rate climbed from 34 percent in 2010 to 47 percent in 2018. After 2010, access advances in SubSaharan Africa outpaced population growth, but the trend reversed recently. Between 2016 and 2018, the number ofpeople in the region lacking access remained almost stable.
At the country level, the 20 countries with the largest access deficits accounted for 78 percent of the total population
without access to electricity in 2018 (Figure ES.3). Nigeria, the Democratic Republic of Congo (DRC), and India had
the three largest deficits: 85 million, 68 million, and 64 million people, respectively. Among the 20 countries with thelargest access deficits, Bangladesh, Kenya, and Uganda showed the greatest improvement since 2010, thanks toaverage annual electrification growth rates in excess of 3.5 percentage points. These three countries were among eightof the 20 countries where the expansion of access to electricity kept pace with population growth between 2010 and2018. The other five were India, Democratic People’s Republic of Korea, Myanmar, Sudan, and Tanzania.
Major disparities in access to electricity are also seen between urban and rural areas. In 2018, the unserved rural
population of 668 million made up 85 percent of the global access deficit. Between 2010 and 2018, access to electricity
in rural areas grew from 70 percent to 80 percent. In urban areas, access is already close to universal (97 percent in2018), but growth in access barely kept up with population growth.
In several countries, expanded off-grid solutions have brought improved access to rural areas. By 2018, renewable
off-grid technologies were providing below Tier 1 electricity services to 136 million people around the world, comparedwith about 1 million people in 2010. These services were provided primarily through standalone home systems andsolar lighting, with mini grids having grown from a niche solution to being widely deployed in off-grid areas that offer
sufficient demand.
Closing the access gap, particularly in Sub-Saharan Africa, will require concerted efforts. Policy frameworks will requireconsistent updates and enforcement to support innovation, such as off-grid solutions and newer business models.
Geospatial analysis undertaken to determine how universal access can be achieved at the least cost show the need for
integrated policies embracing both centralized and decentralized solutions. With significant potential to advance onother SDGs—such as on gender, health, and education—access strategies will succeed only if the technical elements
outlined above take an inclusive approach that leaves no one behind and maximizes the socioeconomic benefits ofelectricity. While the world is coping with the covid-19 pandemic, it is critical to ensure that past gains in electrification
are safeguarded. It might require collective support for utilities, mini grid and off-grid service providers to continue
serving their current clients and allow for future expansion.

4

Tracking SDG 7: The Energy Progress Report 2020

FIGURE ES.2 • Share of population with access to electricity in 2018

Source: World Bank.

FIGURE ES.3 • The 20 countries with the largest access deficit, 2010–18
100

World average, 0.8 pp

World average, 90%

India
90

Access rate 2018 (percentage of total population)

Bangladesh

80

70

Kenya

Pakistan
Myanmar60

Sudan

Nigeria

Democratic People's
Republic of Korea

50
Ethiopia

40

30

UgandaAngolaTanzania

Madagascar

20

Niger

10
Burkina
Faso

0
0.0

0.5

Low income

Mozambique
MalawiChad

1.0

Democratic
Republicof Congo

1.5

2.0

Lower middle income

Bubble size is proportional
to access deficit

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

8.0

Annualized average change, 2010-18 (percentage points)

Source: World Bank.
Note: A country’s “access deficit” is the number of people in the country who lack access to electricity.

Executive Summary

5

Annual increase in access to clean fuels and technologies(percentage points)

0.8

ACCESS TO CLEAN COOKING SOLUTIONS
0.6

The share of the global population with access to clean fuels and technologies for cooking increased from 56
percent in 2010 (uncertainty interval 52–61 percent) to 63 percent in 2018 (56–68), leaving approximately 2.8
billion people without access.1 That number has been largely unchanged over the past two decades owing topopulation growth outpacing the number of people gaining access to clean cooking solutions.
0.4 goal of universal access to clean fuels and technologies for cooking, increases of at least 3 percentage
To achieve the
2000
2005
2010
2015
points annually would
have been needed between
2010 and 2030. Between
2010 and 2018, however,access expanded
at an annualized average of just 0.8 percentage points (–0.2, 1.7) and has steadily slowed since 2012 (to 0.7 percentage
points in 2017 and 2018)—far from the numbers needed to reach the target.

The stagnation in the number of people lacking access to clean cooking globally masks regional trends (Figure ES.4).
Promising improvements were made in Eastern Asia and South-eastern Asia, and in Central Asia and Southern Asia,
but Sub-Saharan Africa moved in the opposite direction, as population growth between 2014 and 2018 outstripped
growth in access by an average of 18 million people a year.
FIGURE ES.4 • Annualized increase in population and in the number of people having access to clean
cooking over the period 2014–18, by region
109.9

World

83.1
8.8

Western Asia andNorthern Africa

8.7
8.5

Sub-Saharan Africa

26.7
41.5

Eastern Asia andSouth-eastern Asia

13.4
42.3

Central Asia andSouthern Asia

23.9
0

20

40

60

80

100

120

Population (millions)
Annualized increase in population with access to clean cooking, 2014-2018

Annuliazed increase in population, 2014-2018

Source: WHO; UN population estimates were used.

The top 20 countries with the largest populations lacking access to clean cooking fuel and technologies accounted for
82 percent of the global population without access between 2014 and 2018.2 Nineteen of the top 20 countries with thelowest access shares are among the world’s least-developed countries, and most of them are in Africa. These countries
increased access by less than 0.1 percentage points annually; in some, access shrank. These trends have combined
to cause access to stagnate in Sub-Saharan Africa, with annualized increases of just 0.4 percentage points for the1
Fuels and technologies considered clean are determined based on the 2014 WHO guidelines for indoor air pollution from household fuelcombustion. These include electricity, liquefied petroleum gas (LPG), natural gas, biogas, solar, and alcohol fuel stoves.
2
The top 20 access-deficit countries are the 20 countries with the highest access-deficit population: Afghanistan, Bangladesh, China, Democratic
People’s Republic of Korea, Democratic Republic of the Congo, Ethiopia, Ghana, India, Indonesia, Kenya, Madagascar, Mozambique, Myanmar, Nigeria,
Pakistan, Philippines, Sudan, Uganda, United Republic of Tanzania, and Viet Nam.

6

Tracking SDG 7: The Energy Progress Report 2020

region between 2010 and 2018. Comparatively, the most significant progress in access to clean cooking fuels was seenin Asia, where annualized increases stood at 1.6 percentage points for Eastern Asia and South-eastern Asia, and 1.5
percentage points for Central Asia and Southern Asia.
Significant variations in access to clean cooking also exist between urban and rural areas owing to disparities ininfrastructure and in availability of clean fuels and technologies. In 2018, access to clean cooking solutions stood at 83
percent (76–87) in urban areas, and at 37 percent (30–45) for rural areas. A slight convergence has been observed,
with disparity falling from 52 percentage points in 2010 to 46 percentage points in 2018. This can be attributed toaccelerated progress in access in rural areas (in particular in Asia), in conjunction with population growth outpacing
access growth in urban areas, particularly in Africa).
As illustrated in Figure ES.5, in low- and middle-income countries, gas (LPG, natural gas, and biogas) has overtaken
unprocessed biomass as the dominant fuel since 2010, reflecting its predominance in urban areas. In urban areas, theuse of electricity for cooking has also risen. In rural areas, unprocessed biomass remains dominant, though its shareis falling.
FIGURE ES.5 • Percentage of people using each cooking fuel type in low- and middle- income countries, forurban areas, rural areas, and overall, 2000–18
Urban

Rural

Overall

Percentage of the population mainly
using each fuel type

80%

60%

40%

20%

0%
2000

2005

2010

2015

Unprocessed Biomass

2000

2005

Charcoal

2010
Coal

2015
Kerosene

2000

2005

Gas

2010

2015

Electricity

Source: WHO Global Household Energy Model.

Among all the SDG 7 targets, slow progress toward clean cooking perhaps presents the greatest cause for concern.
Under current and planned policies, 2.3 billion people would still be deprived of access to clean cooking fuels andtechnologies in 2030, relying instead on traditional uses of biomass, kerosene, or coal as their primary cooking fuel.
This means that nearly a third of the world’s population will continue to be exposed to harmful household air pollution,and many will still be spending many hours gathering fuel. As cooks and fuel gatherers, women and their children aredisproportionately susceptible to these negative effects.
Acceleration of access to clean cooking solutions will require high-level political commitment, ambitious national andsubnational strategies, and an urgent mobilization of investment. Designing and implementing successful commitments
and strategies in turn requires a detailed understanding of the current state and patterns of household energy use. To
achieve this, household surveys must become more comprehensive. In addition to gathering data on grid connectivity,
they should cover off-grid options, impacts on children and women, and all the household fuels and technologies in use
Percentage of the population using each fuel typefor cooking, space heating, and lighting. In
recognitionof these shortcomings, and to support countries in this process,Low- and middle- income countries
WHO and ESMAP at the World Bank have developed a new set of household survey questions. Designed and tested,these survey questions are available for countries to use to better assess the attributes and impacts of householdenergy use for evidence-based decision-making and effective monitoring of household energy use.
4%

3%

37%

Executive Summary

2000

7%

37%

42%

44%
44%

2010

7

2018
49%
4%

10%

0.1%

8%

0.0%

6%

RENEWABLE ENERGY2010 2011 2012 2013 2014 2015 2016 2017

2.0

1.5

EJ

0.2%

1.0

0.5

-0.1%

T

4%

-0.3%

0%

he share of renewable energy in TFEC reached 17.3 percent
in 2017, up from 17.2 percent in 2016 and 16.3 percent
0.0
in 2010 (Figure ES.6).3 This indicates that global use of renewables
has 2012
grown2013
faster2014(at 2.5
percent
2017)
2010 20112015
2016 in2017
than overall global energy consumption (1.8 percent in 2017), extending a trend seen since 2011. The growth-0.2%
2%of renewables is driven primarily by increased consumption-0.5
of modern renewables (that is, renewables other than
traditional uses of biomass). Modern renewables commanded a 10.5 percent share of TFEC in 2017, up from 10.3
percent in 2016 and 8.6 percent in 2010.
-1.0
Modernbioenergy
uses of biomass
The largest increase
the useof renewables
sector, where
their share of
globalelectricity% change inin shareof renewables(left axis)has come in the powerTraditional
consumptionSharereached24.7
percentin2017,
surpassing
the
share
of
renewables
intheheating
sectorforthefirst time.
HydropowerWindof modern renewables (right axis)
The growth rate of almost 6 percent year-on-year was driven primarily by
solar
Lower
hydropower
Solar
PV PV and wind energy.Other
renewables
Share of traditional uses of biomass (right axis)
output (and otherfactors) slowed the growth rate in 2017, sending it below the record 8 percent growth reached in2016. The share of renewables in the heating sector reached 23.5 percent of total final heat consumption in 2017.
This growth can be primarily attributed to uses of modern renewable energy; traditional uses of biomass remained
relatively unchanged in 2017, still accounting for around 14 percent of global heat consumption. In the transport sector,
the share of renewables remained at 3.3 percent in 2017, the majority of which was consumed in the form of liquidbiofuels, predominantly crop-based ethanol and biodiesel. In 2017, the consumption of renewable electricity in thetransport sector represented only 0.3 percent of the sector’s total energy consumption worldwide.

FIGURE ES.6 • Renewable energy consumption by technology and share in total final energy consumption(TFEC), 1990–2017
20%

70

60
15%

50

40
EJ

10%
30

20

5%

10

0

1990

1993

1996

1999

Traditional uses of biomass
Solar PV

2002

2005

Modern bioenergy

Other renewables

2008

2011

Hydropower

2014

2017

0%

Wind

Share of renewables in TFEC (right axis)

Source: International Energy Agency (https://www.iea.org/data-and-statistics) and United Nations Statistics Division (https://unstats.un.org/unsd/
energystats/).

3
The share of renewables in TFEC was previously previously stated as 17.5 percent in 2016. This has been amended to 17.2 percent in this report.
Data revisions by countries in 2020 reflected a fall in solid biomass and charcoal consumption between 2000 to 2016, resulting in a decline in the shareof renewables globally in the historical time series.

8

Tracking SDG 7: The Energy Progress Report 2020

Important regional differences should be noted. Sub-Saharan Africa had by far the highest share of renewable energy
in TFEC for 2017. However, reliance on traditional uses of biomass in the region accounts for almost 85 percent of
its renewable energy consumption and, as already observed, is associated with adverse health and environmental
effects. Owing to the extensive use of modern bioenergy across the power, heat, and transport sectors, in addition to
the region’s reliance on hydropower to generate electricity, Latin America and the Caribbean had the largest share ofmodern renewables among all regions.
At the national level, the share of renewable consumption in TFEC varies widely, depending on resource availability,
policy support, and the impact of energy efficiency on growth in energy demand. Between 2010 and 2017, 13 of theworld’s 20 largest energy consumers expanded their share of renewables (including traditional uses of biomass)(Figure ES.7). The United Kingdom tripled its renewable share in its TFEC. Among the largest 20 energy consuming
countries, Brazil was the leader, with a 45 percent share of modern renewables, followed by Canada at 23 percent.
China remains by far the largest consumer of renewables in absolute terms; its share in 2017 stood at 13 percent. In
several countries, the decrease in total renewable energy share was also driven by reduced traditional uses of biomass.
To boost the share of renewables in energy consumption to a level sufficient to achieve SDG 7 by 2030 and to meetglobal climate objectives, most long-term energy scenarios point toward decarbonization of all end uses, particularly
through increased electrification of the heat and transport sectors. With the right policy support, IEA’s Sustainable
Development Scenario shows that modern renewables could reach a share of 23 percent of TFEC by 2030, supplying
50 percent of electricity generation. IRENA’s Transforming Energy Scenario for 2030 lays out a path toward evenhigher shares of modern renewables: 28 percent overall and 57 percent of electricity generation.
Policies and measures to support the deployment of renewable energy are becoming increasingly common around theworld. In particular, the use of auctions to set electricity tariffs competitively has gained popularity since 2014, owing
chiefly to the ability of well-designed auctions to procure renewables-based electricity at the lowest price while also
fulfilling other social and economic aims of the sponsoring country such as job creation and development of a local
industry. By 2018, more than 106 countries had held a renewable energy auction at some point in time. With the rightpolicies in place, a hike in renewables would be instrumental in advancing not only SDG 7 but also other SDGs, such as
SDG 8 on decent jobs. IRENA’s analysis shows that the number of renewable energy jobs worldwide expanded from 7.3
million in 2012 to 11 million in 2018; and may further triple by 2030.
FIGURE ES.7 • Change in share of renewable energy in total final energy consumption between 2010
and 2017

TFEC = Total final energy consumption.
Source: International Energy Agency (https://www.iea.org/data-and-statistics) and United Nations Statistics Division (https://unstats.un.org/unsd/
energystats/).

Executive Summary

9

ENERGY EFFICIENCY

R

ates of improvement in global primary energy intensity (total primary energy supply per unit of gross domestic
product) have fallen in the past few years, following a period of relative steady growth. Global primary energy
intensity in 2017 was 5.01 megajoules per USD dollar, equivalent to a 1.7 percent rate of improvement since 2016,
the lowest rate since 2010. Nevertheless, recent progress has been greater than historical trends, thanks in part toa range of energy efficiency policies adopted around the world. The average annual rate of improvement in global
primary energy intensity between 2010 and 2017 was 2.2 percent, more than the historical rate of 1.3 percent between
1990 and 2010. To reach the SDG 7.3 target (by doubling the historic improvement trend), the annual improvement to2030 would need to average 3 percent in the years between 2017 and 2030.
Although energy intensity across all end-use sectors improved in aggregate over the 2010–17 period, improvement
rates varied by sector. It is possible to examine the intensity of the sectors using other intensity metrics. These intensity
figures show that transport (freight and passenger) improved during 2010–17, whereas the other sectors show adecrease in intensity improvement over the previous period (1990–2010). The decline in the rate of improvement ismost noticeable in the services and agriculture sectors, where the rate of improvement in energy intensity more thanhalved. The industrial sector’s rate of improvement dropped by about a third. Driving this pattern are the substantial
improvements in energy intensity recorded in emerging economies between 1990 and 2010, which slipped between
2010 and 2017.
Significant geographical differences also exist in energy intensity and recent improvements. Sub-Saharan Africa is themost energy-intensive region; Latin America and the Caribbean the least. Between 2010 and 2017, energy-intensity
improvements continued to be highest in Asia; most countries in the region saw rates of improvement in energy
intensity that were higher than during 1990–2010 and well above the global average (e.g., 3.3 percent in Eastern Asia
and South-eastern Asia). The lowest rates of improvement were found in Latin America and the Caribbean (0.5%),
Northern Africa (0.4 percent) and the Middle East (0.3 percent) (Figure ES.8).
With the recent slowdown in the rate of improvement of energy intensity, the world is slackening the pace required tomeet the SDG 7.3 target, which is to double the global rate of improvement in energy efficiency by 2030. As such, it
is forgoing various benefits. For example, if the world had stayed on track for the target, it could have consumed lessenergy or generated more economic value. And if the world had achieved the target level of intensity for the energy
consumed between 2011 and 2017, global GDP would have been USD 2 trillion per year higher.
By making energy-efficiency measures a policy and investment priority, governments can help the world achieve
SDG 7.3 by 2030. There are numerous examples around the world of successfully implemented policies, ranging fromminimum energy-efficiency standards, financial incentives, market-based mechanisms, capacity-building initiatives,
and regulatory instruments. All of these encourage investment in efficiency measures and help to rebalance energy
markets in favor of cleaner, more efficient operations. Analysis shows that regulatory measures that mandate energy
savings cover only about a third of global energy use. Furthermore, effort will be be needed to harness new digitaltechnologies so that they increase energy efficiency rather than just add to global energy demand. With the rightpolicies in place—ones that maximize the potential of energy efficiency—IEA’s Sustainable Development Scenario
shows that an annual average rate of improvement in energy intensity of 3.6 percent between 2017 and 2030 is indeed
possible (Figure ES.9).

10

Tracking SDG 7: The Energy Progress Report 2020

FIGURE ES.8 • Compound annual average growth rate of primary energy intensity, 2010–17

TPES = Total primary energy supply.
Source: International Energy Agency (https://www.iea.org/data-and-statistics) and United Nations Statistics Division (https://unstats.un.org/unsd/
energystats/).

FIGURE ES.9 • Annual growth rate of primary energy intensity by period, target rate for 2017–30, andpotential for 2017–30 in IEA Sustainable Development Scenario
0%

-1%

-1.3%

-2.1%

-1.7%
-2.6%

-2.6%

-3.0%

-3.6%

-2%

Additional progressto 2030: -0.36%

-3%

-4%
1990-2010
Base period

2011-14

2015

2016

2017

2017-30
target rate
(SDG)

2017-2030 IEA
Sustainable
Development
Scenario

Source: International Energy Agency (https://www.iea.org/data-and-statistics) and United Nations Statistics Division (https://unstats.un.org/unsd/
energystats/).

8

11

Executive Summary

%)

0%

7

) PPP

1%

TRACKING PROGRESS ACROSS TARGETS:
INDICATORS AND DATA

E

ach target is monitored using one or more proxy indicators, in line with the SDG framework devised by the UNSD.4
For example, progress in access is monitored both through the proportion of the population having access toelectricity and the proportion relying primarily on clean fuels and technologies. Similarly, progress in energy
efficiency is monitored through the energy intensity of the economy, measured in terms of primary energy and GDP.
Chapter 6 provides the set of global SDG 7 tracking indicators by country for selected years, preceded by a brief
description of the underlying data work of the custodian agencies. International organizations typically collectand validate data from national administrations; they then further elaborate the data into indicators, adopting
consistent methodologies that ensure comparability across countries. (Indicators derived according to international
methodologies represent global benchmark compilations and are not intended to replace national indicators.)
The work of tracking SDG 7 highlights once more the need for quality data to inform policy at the national, regional,
and international levels, as well as the opportunity to enhance data quality through international cooperation to further
strengthen national capacities. Through a variety of projects worldwide, the custodian agencies actively promote thedevelopment of statistical capacity across countries.
Finally, authors from the custodian agencies would like to acknowledge the work and dedication of all their colleagues
working to collect energy data across national administrations worldwide. It is they who make possible the international
tracking work reflected in this report.

4
The latest full list of targets, indicators, and custodian agencies is available at: https://unstats.un.org/sdgs/files/Tier-Classification-of-SDG-Indicators-11-December-2019-web.pdf

12Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 1: ACCESS TO
ELECTRICITYACCESS TO
ELECTRICITY

Photo: Vincent Tremeau/World BankCHAPTER 1

MAIN MESSAGESThe global trend: The world has made striking progress over the past decade—far more than in previous
decades—in increasing access to electricity. The share of the world’s population having access to electricity grewfrom 83 percent in 2010 to 90 percent in 2018,5 an increase of more than a billion people. During this period,
the number of people without access to electricity fell from about 1.2 billion to 789 million, outpacing the overall
increase in population. Trends from 2016 to 2018 show accelerated electrification (with the average annual rate ofelectrification increasing to 0.82 percentage points) compared with 2010–16 (0.77 points).6



Target for 2030: Despite accelerated progress in recent years, the world will fall short of SDG indicator 7.1.1, whichaims for 100 percent access to electricity by 2030, if the current rate is maintained. Due to the many challenges
facing access-deficit countries, the latest projection shows that about 620 million people would still lack accessto electricity in 2030 (IEA 2019b). To close the gap, the annual rate of electrification would have to rise from thecurrent 0.82 percentage points to 0.87 percentage points for the years 2019 to 2030. Moreover, this projection
does not account for the disruptions of covid-19. These have not yet been quantified, but they will likely affectelectrification, slowing and in some cases even reversing advances (e.g., as utilities and off-grid service providers
face financial difficulties). Governments, hand in hand with the international community, should be prepared tomitigate these adverse effects to safeguard the gains in access.



Regional highlights: The global advance in access to electricity since 2010 masks unequal progress acrossregions, with attention now focusing on Sub-Saharan Africa.7 Latin America and the Caribbean and Eastern Asia
and South-eastern Asia approached universal access, exceeding 98 percent access to electricity by 2018. In
Central Asia and Southern Asia, more than 92 percent of the population had access by 2018. The world’s accessdeficit is increasingly concentrated in Sub-Saharan Africa, which, in 2018, was home to about 548 million people
who lacked access—more than half of the region’s population and nearly 70 percent of the global population
without access. After 2010, access advances in Sub-Saharan Africa outpaced population growth, but the trend has
reversed recently. Between 2016 and 2018, the number of people in the region lacking access remained almost
stable.



Urban-rural distribution in access: Rural populations made up about 85 percent (668 million people) of the
global access deficit in 2018. But, since 2010, they have seen more progress than the urban deficit populations.
Globally, the access rate in rural areas grew from about 70 percent in 2010 to 80 percent in 2018. During thesame period, the rate of urban electrification grew from 95 to 97 percent. While approaching universal access,urban electrification nevertheless faces policy and technical challenges. The obstacles to supplying electricity tosurging urban populations have slowed gains since 2010. Unstable distribution networks have made it difficult toconnect pockets of people in urban cores and in sprawling settlements that ring large cities. In the coming years,
the access rate is more likely to advance in rural areas than in cities.

5
Access to electricity (also referred to as “electrification” or “electrification rate” in the report) refers to the share of the population with access toelectricity out of the total population in the specified time period or geographic area. It is defined as the ability of the end user to consume electricity
for desired services. Where surveys based on the Multi-Tier Framework have been conducted (about 20 countries), access to electricity service at theequivalent of Tier 1 and above (Tier 1+) is considered (ESMAP 2015). Otherwise, electricity access is calculated through binary measurements in existinghousehold surveys, such as the DHS and LSMS (World Bank and IEA 2017). The number of people who gained access between 2010 and 2018 is 1.037
billion.
6

This chapter incorporates both short- and long-term trends in order to better understand the global effects of improved electricity access.

7
United Nations classifications are used for the names and composition of the country groupings used in this report (https://unstats.un.org/unsd/
methodology/m49/); in chapter 5, the report uses IEA’s World Energy Outlook classifications.

15



The top 20 countries with access deficits: In 2018, 20 countries accounted for 617 million people without
access—78 percent of the worldwide deficit in that year. Achieving universal access will require sustained efforts
to bridge electrification gaps in these countries. Nigeria and the Democratic Republic of Congo had the world’s
largest access deficits in 2018, with 85 and 68 million people, respectively, lacking access. India was third with
about 64 million people. Over the 2010–18 period, electrification efforts in Nigeria and the Democratic Republicof Congo (DRC) lost ground to population growth, leading to net increases of 3 million and 12 million people,
respectively, lacking access to electricity by 2018. Among the 20 largest access-deficit countries, Bangladesh,
Kenya, and Uganda showed the most improvement since 2010. Expansion of access kept pace with population
growth in just 8 of the 20 countries during the period; in addition to the three just mentioned, those countries wereIndia, Democratic People’s Republic of Korea, Myanmar, Sudan, and Tanzania.



Decentralized renewable energy: By 2018, about 35 million people had access to off-grid sources of electricity atTier 1 and above (Tier 1+); close to 136 million people had access to solutions below Tier 18 (IRENA 2019a; GOGLA2019). The Tier 1+ sources were mostly standalone home systems and solar lighting, with mini grids becoming a
growing source. By 2018, the adoption of off-grid energy sources had tripled worldwide from 2010 levels. Overall,
the two major access-deficit regions (Sub-Saharan Africa and Central Asia and Southern Asia) are embracing
off-grid technologies as least-cost alternatives to the grid.

8
Under the MTF classification, households with access below Tier 1 have electricity for less than 4 hours per day, supplemented by off-grid solar
devices or rechargeable batteries.

16

Tracking SDG 7: The Energy Progress Report 2020

ARE WE ON TRACK?

A

s of 2018, 90 percent of the world’s population had access to electricity (Figure 1.1). From 2010 to 2018, theglobal population without access to electricity shrank from almost 1.2 billion to 789 million. Between 2016 and2018, an average of 136 million people gained access to electricity each year, substantially more than the averageannual population growth of 84 million for the same period. The progress between 2016 and 2018 also represented an
acceleration from the annual increase in electrification of 127 million people seen between 2010 and 2016. Yet global
progress hides glaring disparities among countries and regions. For instance, the least-developed countries fall wellbehind the global average.9 By 2030 (before accounting for covid-19 effects), about 93 percent of the global population
are projected to have access to electricity; this means that close to 620 million people would lack it (IEA 2019b).
The shortfall in meeting the target reflects the complexities involved in bringing electricity to unserved populations—complexities that extend to affordability, reliability, and the cost of deploying last-mile solutions, especially in lowincome, remote, or conflict-affected countries. As of 2018, 57 percent of those without access lived in low-income
countries, 30 percent in fragile and conflict-affected areas.10
FIGURE 1.1 • Percentage of population with access to electricity
0%

100%

Status in 2000

78%

Progress between 2000 and 2010

83%
90%

Progress between 2010 and 2018
Projected progress up to 2030

93%
100%

Remaining gap to 2030 SDG7 target

Source: World Bank, IEA.

92%

9

4

80%

78%

3
2

6.8

5.7

4.7

78%
76%
74%

1

72%

Share of population with access to electricity

Population (billion)

Since 2010, 52 countries—most of them in Latin America and the Caribbean—have reached universal 90%
access, whereas
90%
8 88—concentrated in Sub-Saharan Africa, Central Asia, and Southern Asia—were still short of the goal in 2018.
another
Fewer than half of the latter accelerated their annual electrification rates by more than 2 percentage points88%
between0.8
2010 7and 2018, including just 8 of the top 20 access-deficit countries (Figure 1.2). On a more positivenote, nearly86%
1.1managed electrification rates in excess of population
75 percent of the 88 countries still short of universal access
6
84% 2010,
growth. In Sub-Saharan Africa, an annual average of more than 26 million people gained access each year after
1.3
improving
the regional rate to 47 percent in 2018. In Central Asia and Southern Asia, 1.8 billion people, making up more
5
82%
83%
than 92 percent of the region's population, had gained access by 2018.

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

9
The
70%
0 list of least-developed countries for 2018 can be found here: https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/
publication/ldc_list.pdf.
10Countries with a per capita GNI of less than USD 1,025 are classified as low-income (https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups). Countries affected by violent conflict are identified based on a threshold number of conflict-related deaths relative
to the topopulation
The
With accesselectricity(https://www.worldbank.org/en/topic/fragilityconflictviolence/brief/harmonized-list-of-fragile-situations).
Without access to electricity
Share of population with access to electricity
two categories are not mutually exclusive.

CHAPTER 1 • Access to electricity

1.0
0.9

17

FIGURE 1.2 • Annual increase in access to electricity rate in access-deficit countries, 2010-18 (percentage
points)

Source: World Bank.

18

Tracking SDG 7: The Energy Progress Report 2020

LOOKING BEYOND THE MAIN INDICATORST

his chapter explores changes in access to electricity between 2000 and 2018, comparing progress acrosssocioeconomic and geographical contexts in response to electrification efforts. The aim of the analysis is toinform efforts to achieve the 2030 target and to sustain gains in access.

After analyzing access trends using data for the 2000-2018 period, the chapter provides policy insights based on aliterature review and country case studies.11 The methodology employed is explained at the end of the chapter.
0% AND POPULATIONACCESS

100%

Despite major progress since 2010, the current pace of electrification is still not fast enough to meet the 2030 target.
The global electrification rate has progressed steadily, rising from 83 percent of the world’s population in 2010 to 90
percent in 2018 (Figure 1.3). During this same period, the population without access to electricity fell from 1.2 billion
to 789 million. Compared with previous decades, the pace of electrification has accelerated since 2010. Between 2016
and 2018, however, electrification grew by just 0.82 percentage points per year, lower than the average annual increase
Status in(before
2000 the onset of covid-19) to achieve universal access by 2030 (0.87 percentage points; Figure
believed necessary
78%1.4). The last
mile of theroad 2000
to universal
access will be especially challenging in view of the difficulty of reaching theProgress
betweenand 2010
83%
populations that remain unserved. In addition, affordability and reliability remain salient issues for many countries
Progress
between
2010
and
2018
moving toward the target. According to the 2018 Regulatory Indicators for Sustainable Energy90%(RISE), the poorest 40
percent of households
in half ofaccess deficit countries spent more than 5 percent of their 93%
monthly household
Projected progress
upthe
to 2030
expenditure on 30 kilowatt-hours (kWh) of electricity12 (ESMAP 2018). One-third of the access-deficit 100%countries face
Remaining gap to 2030 SDG7 target
more than one disruption per week in electricity supply, with disruptions lasting more than four minutes on average.
FIGURE 1.3 • Gains in electricity access, 2000–18 (billions of people and share of population with access)
90% 90%

8

0.8

5
4

84%

1.3
83%

82%
80%

78%

3
2

88%
86%

1.2

6

6.8

5.7

4.7

78%
76%
74%

With access to electricity

Without access to electricity

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

70%
2003

0
2002

72%

2000

1

2001

Population (billion)

7

Share of population with access to electricity

92%

9

Share of population with access to electricity

Source: World Bank.

ualized average change(percentage points)

11
Access to electricity data in this chapter mostly comes from the World Bank’s Global Electrification Database: https://databank.worldbank.org/
source/world-development-indicators.
1.0
12
The World Bank’s Regulatory Indicators for Sustainable Energy can be found at https://www.worldbank.org/en/topic/energy/publication/rise---regulatory-indicators-for-sustainable-energy.
Electricity is considered affordable if a household does not have to spend more than 5 percent of its
0.9
total monthly income to purchase it (World Bank and IEA 2015). The definition of subsistence consumption varies by region but has been defined in the
0.8 per month (Kojima and Trimble 2016).
range of 30 kWh

0.7

0.6
CHAPTER 1 • Access to electricity
0.5
0.4
0.3

19
0.77

0.54

0.82

0.87

70%

With access to electricity

Without access to electricity

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

0

Share of population with access to electricity

FIGURE 1.4 • Average annual increase in access to electricity (in percentage points) required to reach
universal access by 2030
1.0
0.9Annualized average change(percentage points)

0.8
0.7
0.6
0.5
0.4

0.77

0.3

0.82

0.87

2016-20182019-2030

0.54

0.2
0.1
0.0
1990-2010
Base period

2010-2016

Source: World Bank.
Note: The 2019–30 annual increase required to achieve the target does not include potential impacts from the covid-19 pandemic.

Between 2010 and 2018, electrification accelerated faster than demographic growth worldwide (Figure 1.5). This
trend was confirmed between 2016 and 2018, as electricity reached 136 million new people on average annually, while
the world population grew by 84 million (Figure 1.6). The increase in population with access is traceable chiefly toelectrification efforts in Central Asia and Southern Asia, where an annual average of 66 million people gained accessto electricity between 2010 and 2018. For Sub-Saharan Africa, even though electrification outpaced population growth
for the period, recent growth in access (2016 to 2018) fell below population growth. This resulted in a net annual
increase of almost 0.3 million people without access to electricity in the region between 2016 and 2018, driven largely
by a slowdown in two large access-deficit countries: DRC and Nigeria.
FIGURE 1.5 • Pace of increased electricity access vs. pace of global population growth, 2000–18 (index,
2000 = 100)
155
145
135
125
115
105

Pace of increased access to electricity (World)

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

95

Pace of population growth (World)

Source: World Bank.

20

Tracking SDG 7: The Energy Progress Report 2020

160FIGURE 1.6 • Annual incremental increases in electrification and population, 2016–18, by region
160
140

136

Population (million)

120
100

84

80

66
60
40

24

20
0

World

Central Asia
and Southern Asia

22

26.7 27.0
14

Eastern Asia
andSouth-eastern
Asia

8

6

Latin America
and theCaribbean

Annualized Incr emental population with acces s, 2016-2018

4

3

Northern
Americaand Europe

1

8

1

Oceania

Sub-SaharanAfrica9Western Asia
andNorthern Africa

Annualized Incr emental population, 2016-2018

Source: World Bank.

Low-income countries and those affected by fragility, conflict, and violence are lagging behind. Within the group of lowincome countries, the population share with access to electricity grew from 30 percent in 2010 to 43 percent in 2018.
Between 2016 and 2018, population growth slightly outpaced growth in access to electricity. Globally, more than halfof the unserved population live in low-income countries. The global access deficit has been increasingly concentrated
in those countries, with their share in the unserved population growing from 37 percent in 2010 to 53 percent of the
global population without access in 2018 (420 million). In fragile and conflict-affected countries, the access rateincreased from 48 percent in 2010 to 62 percent in 2018. Yet, over the short-term (2016 to 2018) in these countries,
the population grew faster than electrification, with a net increase of almost 2 million annually in the unconnected
population. In 2018, almost one-third of unserved people lived in fragile and conflict-affected contexts (233 million).
These results reflect a major push toward electrification in middle-income countries, with modest progress in lowincome countries and fragile and conflict-affected settings. They also show that the push to reach the remaining
unserved population is becoming even more challenging. Access to more and better data would help to inform policy
in fragile and low-income environments that present the most complex challenges (box 1.1).

CHAPTER 1 • Access to electricity

21

BOX 1.1 • MEASURING ACCESS TO ELECTRICITY FROM THE NIGHT SKY
Satellite images captured at night are proving to be a promising source of data for measuring access to electricity.
The images show the emission of light around the globe, providing a record dating back to 1992 (between
the DMSP-OLS and VIIRS platforms). Nonhuman sources of light, such as lunar reflections and fires, can beremoved, producing satellite data with compelling images of urbanization and access to electricity. Analysis ofsatellite imaging can reduce the lag in tracking the progress of electrification, particularly in fragile and conflictaffected countries where household surveys and censuses are conducted infrequently and irregularly, leaving
substantial data gaps.
To create the image in Figure B1.1, a year’s worth of night-time lights imagery is processed to create a single
indicator of the likelihood of electrification (shown by the shaded green squares), with a resolution of around 500
meters. The images are further filtered to find points significantly brighter than their surroundings, producing
regions of access (black outlines). By overlaying this with population data (red pixels), it is possible to create
disaggregated estimates of access. It is also possible to go further, using additional data to quantify not only
access but also the percentage of connections within each area. Satellite imagery can therefore complement
the end-user data available from household surveys such as the Multi-Tier Framework.a
The approach has several limitations, however, such as coarse resolution and large regional differences, whichmust be overcome through further research. Granularity is limited by the amount of light that can be picked up
from space. Industrial complexes and streetlights are bright, whereas satellite sensors may not be able to pickup light emitted from houses or offices. Off-grid sources may be particularly hard to capture because of dimmer
light.
FIGURE B1.1 • Night-light areas around Asmara, Eritrea

Source: World Bank; MapBox Satellite; Facebook HRSL; NOAA VIIRS.
a. The Multi-Tier Framework (https://www.worldbank.org/en/topic/energy/publication/energy-access-redefined) looks at the multiple
dimensions of access to capture information about the quantity and quality of services. It also captures the multiple modes of delivering
energy access from grid to off-grid and the range of cooking methods and fuels people use.

22

Tracking SDG 7: The Energy Progress Report 2020

THE ACCESS DEFICIT
While the number of people worldwide without access to electricity fell steadily from 1.2 billion to 789 million between
2010 and 2018, the overall trend hides important regional disparities. The decline was most significant in Central Asia
and Southern Asia, where the deficit shrank from 441 million in 2010 to 152 million in 2018 (Figure 1.7). During the same
period, the global deficit became increasingly concentrated in Sub-Saharan Africa. That region’s share grew from 48
percent of the overall global deficit in 2010 to almost 70 percent in 2018; within the region, 548 million people lacked
access in 2018. The region’s deficit increased slightly between 2016 and 2018 (Figure 1.8), as electrification efforts fellbehind population growth, particularly in Burkina Faso, DRC, Niger, and Nigeria.
FIGURE 1.7 • Evolution of the access deficit (millions
of people), 2000–18

FIGURE 1.8 • Evolution of electricity access(percentage of population with access), 2000–18

80

1,200
1,000
800
600

92

90

1,352

789
607
548

477

400

152

200
0

90

77

70
60

59
47

50
40
30 25
20
10

2017

2018

2015

2016

2013

2014

2011

2012

2010

2009

2007

2008

2005

2006

2003

2004

2001

2002

2000

0
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018

1,400

100

Population with access (%)

Population without access (millions)

1,600

World

World %

Central Asia and Southern Asia

Central Asia and Southern Asia %Sub-Saharan Africa %Sub-Saharan Africa

Source: World Bank.

Latin America and the Caribbean is approaching universal access; in 2018, the level of access to electricity there was 98
percent, leaving just 11 million of the region’s people without access, most of them in Haiti, Peru, Guatemala, Honduras,
and Nicaragua. Eastern Asia and South-eastern Asia also showed improvement, exceeding 98 percent access in 2018.
These regions are expected to reach universal access ahead of the 2030 schedule, provided they surmount the hurdleof last-mile connectivity posed by affordability and cost of supply.

THE URBAN-RURAL DIVIDEIn 2018, the world’s rural areas continued to have lower levels of access to electricity (80 percent, with 668 million
people unserved) than urban areas (97 percent; 121 million). The pace of electrification picked up in rural areas
between 2010 and 2018, whereas it remained steady in urban areas (Figure 1.9). Between 2016 and 2018, the focus
on electrifying the countryside brought power to over 52 million new residents on average each year, far outpacing
rural population growth over the same period. Rural electrification accelerated at a pace more than six times that ofrural population growth in Central Asia and Southern Asia between 2016 and 2018. In Sub-Saharan Africa, the paceof rural electrification matched that of rural population growth (Figure 1.10), although about 70 percent of the world’s
unelectrified rural population lived in Sub-Saharan Africa.
Globally, despite slower growth in access, urban electrification brought access to more than 83 million urban residents
on average each year between 2016 and 2018 (compared with population growth of 80 million). In Sub-Saharan Africa,
electrification in urban areas dipped below population growth. As a result, in 2018, most of the world’s unelectrified
urban population lived in Sub-Saharan Africa (76 percent in 2018) (Figure 1.11). A vast majority of this unserved urban

CHAPTER 1 • Access to electricity

23

population in Sub-Saharan Africa lived in low-income and fragile and conflict-affected countries (62 percent and 75
percent, respectively). The last-mile issues for large cities are posed by populations residing in vast informal settlementsthat are unlikely to be attractive customers for utilities, as they present thorny barriers pertaining to legality, ownership,
low demand, and housing type. Electrifying new areas is generally more newsworthy than densifying existing areas
already connected. Additionally, donors have tended to push for rural electrification.
FIGURE 1.9 • Gains in electricity access in urban and rural areas, 2000, 2010, and 2018 (billions of people
Urban
and share of population
with access)
Rural

0.1

7
6
6
5

0.1

94%
94%

0.2

3
2

0.2

0

0.1

97%

96%
94%

97%

94%
92%

0.1
0.1

4
3

1
0

96%

98%
96%

96%

5
4

2
1

100%
98%

0.1

92%
90%

0.1

90%
88%

0.1
3.4

2.7

86%
84%

4.1

3.4

2.7

88%
86%

4.1

84%
82%

0.7

4
4

63%

3

63%
1.2

3

0.7

70%
1.0
1.0

2.1

1

2.1

0

90%
80%

80%

80%
70%

80%

70%
60%

0.7

60%
50%

0.7

50%
40%
40%
30%

2
1

1.3

70%

1.2

2

80%
With access to electricity
2000
2010
2018
Without access to electricity
With access to electricity
Share ofaccesspopulation
with access to electricity
Without
to electricity

2018

1.3

5

0

2010

100%
90%

5

82%
80%

2000

100%

Rural

6

Population(billions)
Population(billions)

PPopulation(billions)
PPopulation(billions)

8
7

6

2.7

2.3
2.3

2000

30%
20%

2.7

2010

20%
10%
10%
0%

2018

With access to electricity
2000
2010
2018
Without access to electricity
With access to electricity
Share ofaccesspopulation
with access to electricity
Without
to electricity

Annualofincreasein access(pp) to electricity
Share
population
with accessAnnualin access(pp) to electricity
Share ofincrease
population
with accessAnnual increase in access (pp)Annual increase in access (pp)ShareShareof populationof population
with accesswith accessto electricity
to electricity

100%

Urban

ShareShareof populationof population
with accesswith accessto electricity
to electricity

80%Source: World Bank.

FIGURE 1.10 • Annual incremental growth in access and population in urban and rural areas of Sub-SaharanAfrica and Central Asia and Southern Asia, 2016–18

70
80

80

83
World

50 Central Asia and Southern Asia
46

18

45
50
40
45
35
40
30
35
25
30
20
25
15
20
10
15
5
10
0
5

16
18

83

60
70

52

50
60

52

40
50
30
40
20
30
10
20

4

0
10

4

0

Urban

Rural

Annualized
UrbanIncremental population,
Rural
2016-2018
Annualized
Annualized Incremental
Incremental population,
population
2016-2018with access, 2016-2018

Annualized Incremental population
with access, 2016-2018
Source: World Bank.

24

0

Sub-Saharan Africa

46
Population
Population(millions)(millions)

Population
Population(millions)(millions)

80
90

80

Central Asia and Southern Asia

Population
Population(millions)(millions)

90

World

21
17

21

17

7
7

Urban

14
16

Sub-Saharan Africa
16
16
16

16

12
14

11

10
12

11

12
12

8
10
6
8
4
6
2
4

Rural

Annualized
Incremental population,
Urban
Rural
2016-2018
Annualized
Incremental
population,
Annualized Incremental population
2016-2018with access, 2016-2018
Annualized Incremental population
with access, 2016-2018

0
2
0

Urban

Rural

Annualized Incremental population,
Urban
Rural
2016-2018
Annualized
Incremental
Annualized Incremental population,
population
2016-2018with access, 2016-2018
Annualized Incremental population
with access, 2016-2018

Tracking SDG 7: The Energy Progress Report 2020

FIGURE 1.11 • Regional shares of the global access deficit, in total and along the urban-rural divide, 2000,
2010, and 2018
Total

Urban

7%

8%

Rural

7%
28%

2000

45%

35%

47%

34%
48%

16%
12%

13%

6%

6%

6%

20%

38%
2010

41%
14%

48%

46%

60%
8%

7%

3%
6%

5%
19%

6%

15%
5%

2018

70%

Central Asia and Southern Asia

22%
4%

77%

Sub-Saharan Africa

68%

Eastern Asia and South-eastern Asia

Rest of the world

Source: World Bank.

OFF-GRID ELECTRIFICATION
Progress is being made to improve the accuracy of data on off-grid electrification. As of today, supply-side data isavailable in databases maintained by the International Renewable Energy Agency (IRENA) and the association of
producers of off-grid solar energy (GOGLA), in addition to demand-side figures made available through the Multi-Tier
Framework.
As of 2018, more than 35 million people had Tier 1+ electricity service access through standalone home systems
or renewable-based mini grids (IRENA 2019a; GOGLA 2019). The population with access to standalone systems
providing Tier 1+ service increased almost four times between 2010 and 2018; although it started from a low basis,the population with access to solar mini grids providing Tier 1+ access quintupled between 2010 and 2018. In 2018,
standalone systems producing 11–50W and above made up 72 percent of Tier 1+ off-grid access; the rest came frommini grids.

CHAPTER 1 • Access to electricity

25

The number of people gaining Tier 1+ access through mini grids exceeded 3 million in 2018. mini grids have grownfrom a niche solution to widespread deployment in off-grid areas that offer sufficient demand to sustain a mini gridbusiness. Leading developers are leveraging transformative technologies and economic trends to build portfolios of“third-generation” mini grids at unprecedented scale that provide high-quality, affordable electricity (ESMAP 2019).
In the off-grid solar sector, new markets and a shift toward higher-priced and larger pay-as-you-go–enabled products
have driven the rapid growth in the sector’s sales (ESMAP 2020).
As of 2018, about half of the 20 countries with the highest levels of Tier 1+ off-grid access were in Sub-Saharan Africa,
whereas only four were from Central Asia and Southern Asia. In 2018, Bangladesh, Fiji, Mongolia, Nepal, and Rwanda
saw more than 5 percent of their population gain Tier 1+ access from off-grid sources (Figure 1.12).
By 2018, below–Tier 1 solutions were providing basic electricity services to 136 million people globally, comparedwith about 1 million people in 2010. Some of the access-deficit countries that provided more than 10 percent of their
population with such access were Kenya, Rwanda, Somalia, Uganda, and Vanuatu (Figure 1.13). Below–Tier 1 solutions
are an important pre-electrification step enabling people can gain access to basic electricity for which they would
otherwise have to wait for years.
FIGURE 1.12 • Top 20 countries with the highest rates of access to off-grid supply (Tier 1 or higher), 201810%
Share of population connected to mini biogas (Tier 2+)

9%
Share of population connected to off-grid supply

Share of population connected to mini hydro (Tier 2+)
8%

Share of population connected to solar mini grids (Tier 2+)
Share of population connected to solar mini grids (Tier 1)

7%

Share of population using solar home systems (>50 W, Tier 2+)
Share of population using solar home systems (11-50 W, Tier 1)

6%
5%
4%
3%
2%
1%

Cuba

Tajikistan

Cambodia

Guinea-Bissau

BhutanCameroon

MoroccoMali

Liberia

Sierra Leone

Tanzania

Kenya

UgandaAfghanistan

VanuatuFiji

Bangladesh

RwandaMongolia

Nepal

0%

Source: IRENA, GOGLA.

opulation connected to off-grid solar supply

100%

26

90%
80%

Share of population using solar lights (<11 W)

70%
60%
50%
40%
30%

Tracking SDG 7: The Energy Progress Report 2020

Cu

Tajikist

Cambo

Guinea-Biss

Bhut

Camero

Moroc

Libe

Sierra Leo

Tanza

Ken

Ugan

Afghanist

Vanu

Banglad

Rwan

Mong

Ne

FIGURE 1.13 • Top 20 countries with the largest share of solar lighting systems (below Tier 1), 2018

Share of population connected to off-grid solar supply

100%
90%
Share of population using solar lights (<11 W)

80%
70%
60%
50%
40%
30%
20%
10%

Mali

Tanzania

Sierra Leone

Ethiopia

Zimbabwe

India

MalawiBurkina Faso

Somalia

JordanBenin

Papua New Guinea

SenegalUgandaSamoa

Rwanda

Mauritius

Fiji

Kenya

Vanuatu0%

Source: IRENA, GOGLA.

COUNTRY TRENDS
Of the unserved population at the end of 2018, more than 617 million people (78 percent) lived in the 20 largest accessdeficit countries (as determined by the number of people lacking access), also called “high-impact countries” (Figure1.14). For that reason, closing the access deficit globally will depend on efforts focused on these countries.
In 2018, Nigeria replaced India as the country with the largest population without access. For the first time since tracking
began, the top two deficit countries (Nigeria and the Democratic Republic of Congo) are in Sub-Saharan Africa. The
pace of electrification in Nigeria (+1.1 percentage points annually since 2010, reaching 57 percent access in 2018) was
not enough to keep up with population growth (+3 percentage points annually). The access deficit increased by almost
3 million people since 2010, bringing to 85 million the number of people lacking access to electricity in 2018. The DRC,
too, struggled to keep its electrification efforts on par with population growth. Between 2010 and 2018, access rates
in the country rose only by 6 percentage points, with the result that the access deficit grew by almost 12 million from2010 to reach a total of 68 million people in 2018. By contrast, India made major progress between 2010 and 2018 byaccelerating its efforts to achieve universal access. Despite an access rate of 95 percent, 64 million Indians were still
without access. In another change, Yemen replaced Mali on the list of top 20 access-deficit countries.
Almost three-quarters of the 20 major access-deficit countries expanded electrification at a rate of more than one
percentage point each year since 2010. Only eight of them, however, electrified rapidly enough to outpace population
growth. These were Bangladesh, India, Kenya, Democratic People’s Republic of Korea, Myanmar, Sudan, Tanzania, andUganda. Twelve countries, mainly in Sub-Saharan Africa, could not outpace population growth: Angola, Burkina Faso,
Chad, Democratic Republic of Congo, Ethiopia, Madagascar, Malawi, Mozambique, Niger, Nigeria, Pakistan, and Yemen.
Some larger countries with unserved populations of more than 50 million in 2018—such as Pakistan—have electrified
at rates of less than one percentage point per year since 2010, resulting in increased access deficits (Figure 1.15). As aresult of conflict, Yemen has seen its access rate shrink since 2010.

CHAPTER 1 • Access to electricity

27

FIGURE 1.14 • Share of population and total population without access, top 20 access-deficit countries andrest of the world, 2018
100%

Country and population without access to electricity
Nigeria - 85 million
Democratic Republic of the Congo - 68 million
India - 64 million
Pakistan - 61 million
Ethiopia - 60 million
United Republic of Tanzania - 36 million
Uganda - 25 million
Bangladesh - 24 million
Mozambique - 20 million
Madagascar - 19 million
Niger - 18 million
Myanmar - 18 million
Angola - 17 million
Burkina Faso - 17 million
Sudan - 17 million
Malawi - 15 million
Chad - 14 million
Democratic People's Republic of Korea - 13 million
Kenya - 13 million
Yemen - 11 million
Rest of the world - 172 million

Share of population without access to electricity

90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0

31

60

91

121 152 182 213 244 274 305 335 366 397 425 456 486 517 547 578 609 639 670 700 731 762 790
Population without access (million)
Low income

Lower middle income

Rest of the world

Source: World Bank.

FIGURE 1.15 • Electricity access in the top 20 access-deficit countries by population, 2010–18
Access deficit, 2018 (million)
050

Access rate, 2018 (%)
100

Nigeria0

Democratic Republicof the Congo
India

64

Democratic Republicof the Congo
India

Pakistan

61

Pakistan

Ethiopia

60

68

United Republicof Tanzania

50

Nigeria

85

19
95
71

Ethiopia

45

25

UgandaBangladesh

24

Bangladesh

Mozambique

20

Mozambique

Madagascar

19

Madagascar

Niger

18

Niger

Myanmar18

MyanmarAngola17

AngolaBurkina Faso

17

Burkina Faso

Sudan

17

Sudan

Malawi

15

Malawi

18

Chad

14

Chad

12

13
13

Democratic People's
Republic of Korea
Kenya

Yemen

11

Yemen

World Average

43

1
2

Pakistan

0.1

Ethiopia

1
3
4

Uganda85

Bangladesh

4

31

Mozambique

26

Madagascar

1

Niger

1

18

2

Myanmar

66
43
14

2

Angola1

Burkina Faso

0.1

Sudan

60

2

Malawi1

Chad1

Democratic People's
Republic of Korea
Kenya

48
75

Yemen

62
90

World Average

41

Democratic Republicof the Congo
India

United Republicof Tanzania

36

UgandaDemocratic People's
Republic of Korea
Kenya

Nigeria57

United Republicof Tanzania

36

100

Annualized increase in access,2010 - 2018 (percentage points)
-5
0
5
10

2
7
-1

World Average

0.3

Source: World Bank.
Access deficit, 2018 (million)

28

0

50

Annualized increase in access,2010 - 2018 (pp)Access rate, 2018 (%)
100

0

50

100

Tracking SDG 7: The Energy
0 Progress Report 2020
5

Burundi10

Burundi11

Burundi

1

Chad

14

Chad

12

Chad

1

Myanmar

18

MyanmarAngola17

AngolaBurkina Faso

17

Burkina Faso

Sudan

17

Sudan

Malawi

15

Malawi

Myanmar

66
43
14

2

Angola1

Burkina Faso

0.1

Sudan

60
18

2

Malawi1

The least-electrified
countries
are all in Sub-SaharanChad
Africa; 12almost all are among the least-developed
countries(Figure
Chad
Chad
1
14
1.16).
Burundihadthelowestaccess
rates
in
2018:
11
percent
and12
percent,
respectively,
andlimited
Democratic
People's
Democratic
People's
Democratic
People'sand Chad48
213
Republic of Korea
Republic of Korea
Republic of Korea
improvement
since 2010. In Sub-Saharan Africa, Benin,
Burkina Faso,75Burundi, Chad, theKenya
DRC, Niger, and Zimbabwe
Kenya
Kenya
7
13
have had annual electrification rates of less than one percentage point since 2010. On the other hand, Uganda’s annual
Yemen
Yemen
Yemen
-1
62
11
increase in electrification
was almost four percentage points, enabling the country to shrink its deficit.
World Average

90

World Average

4World Average

0.3

FIGURE 1.16 • Electricity access in the 20 least-electrified countries, 2010–18
Access deficit, 2018 (million)
050

Annualized increase in access,2010 - 2018 (pp)Access rate, 2018 (%)
100

0

50

0

100

5

Burundi10

Burundi11

Burundi

Chad

14

Chad

12

Chad

1

Burkina Faso

17

Burkina Faso

14

Burkina Faso

0.2

Niger

18

Niger

18

Niger

1

Malawi

15

Malawi18

Malawi19

Democratic Republicof the Congo
Madagascar

Democratic Republicof the Congo
Madagascar

68

Democratic Republicof the Congo

19
26

Madagascar

Liberia4

Liberia

26

Liberia

Sierra Leone

6

Sierra Leone

26

Sierra Leone

South Sudan

South Sudan
Guinea-Bissau

8
1

MozambiqueCentral African
Republic
Rwanda20

South Sudan

29

Guinea-Bissau

Mozambique

31

8
10
36
10

1
1
1
3
2
3
3

Mozambique

32

Central African
Republic

35

RwandaSomalia
United Republicof Tanzania
Zambia35

40

Somalia
United Republicof Tanzania
ZambiaCentral African
Republic
Rwanda3

Somalia
United Republicof Tanzania
Zambia28

Guinea-Bissau

1

36

2
3
3
2
3
2

Zimbabwe

9

Zimbabwe

41

Zimbabwe

0.2

Benin

7

Benin

42

Benin

1

Uganda43

UgandaUgandaWorld average

25
4World average

90

World average

4
0.3

Source: World Bank.

Three countries (Afghanistan, Cambodia, and Kenya) have electrified at rates exceeding 7 percentage points annually
since 2010 (Figure 1.17). The three followed different strategies. In Afghanistan, electrification has been driven principallyby humanitarian groups, whose efforts have transformed it into the country with the most mini grids in addition toimpressive off-grid solar penetration (ESMAP 2019). Cambodia and Kenya relied more on integrated planning thatcombined grid and off-grid electrification, public financing, and incentives for the private sector. RISE suggests that,since 2010, programs supporting mini grids and standalone systems have benefited from a strong regulatory push,
more so than grid electrification. Cambodia’s off-grid expansion proved significant in improving access in rural regions(ESMAP 2018).13
These experiences show that, regardless of a country’s stage in the process, rapid electrification is possible, even ina fragile context; an enabling environment is key. This lesson is borne out in countries with low access rates, such as
Rwanda and Liberia, as well as in countries with high rates, such as India and the Lao People’s Democratic Republic.

13
According to the World Bank’s 2018 Regulatory Indicators for Sustainable Energy, found at https://www.worldbank.org/en/topic/energy/publication/rise---regulatory-indicators-for-sustainable-energy.

CHAPTER 1 • Access to electricity

29

FIGURE 1.17 • Electricity access in the 20 fastest-electrifying countries by annualized increase, 2010–18
Access deficit, 2018 (million)
0

20

40

0

Cambodia1

Cambodia

Afghanistan

0.5

Afghanistan

Kenya

13

Timor-Leste

Papua New Guinea

4Papua New Guinea

Kiribati

0.1

Kiribati

Solomon Islands

0.2

Solomon Islands

Eswatini

0.3

2South Sudan

Nepal

2

Mali

9

Guinea-Bissau

100

3
4

4

Uganda4

Lesotho44

Lao People's
Democratic Republic
Bhutan33South Sudan

3

Congo

3

69
94
35

Nepal

3

Rwanda3

Mali

3

Guinea-Bissau

29

Guinea-Bissau

3Central African
Republic
World average

32

Central African
Republic
World average

51

Mali

1

Eswatini

Bangladesh

28

Nepal
Rwanda8

Central African
Republic
World average

98

Congo

Rwanda485

Lao People's
Democratic Republic
Bhutan8

Congo

5

Solomon Islands

77

24

0.1

South Sudan

67

5

Kiribati

100

47

7
6

Papua New Guinea

59

Lesotho7

Timor-Leste

86

Bangladesh

10
8

Kenya

75

43

5

Afghanistan

99

Uganda0.1

0Cambodia92

25
1Bangladesh
Lao People's
Democratic Republic
Bhutan100

Eswatini

UgandaLesotho

50

Kenya

0.2

Timor-Leste

Annualized increase in access,2010 - 2018 (pp)Access rate, 2018 (%)

90

3
0.3

Source: World Bank.

100%
90%

80%

80%
70%
60%
50%

37%

40%

25%

30%

25%

20%
10%

0%

0%

Bangladesh(2018)

Burkina Faso
(2018)

5%

1%
0%

Cameroon(2018)

Chad(2018)

10%
7%

10%

10%
0%

0%

Access rate of selected refugee camps

30

Kenya
(2015)

Rwanda(2018)

Tanzania(2019)South Sudan(2019)

Access rate of host communities

Tracking SDG 7: The Energy Progress Report 2020

POLICY INSIGHTS

T

he world has a decade to meet the SDG 7 call for universal access to electricity. Now more than ever, efforts must
be made to accelerate electrification in access-deficit countries. The covid-19 crisis has further accentuated theneed for reliable, affordable access—in health institutions in particular (box 1.3), but also for water pumping,schools, and community resilience. Recent trends have shown, however, that it is hard to sustain the pace ofelectrification through to the last mile, or even the last few miles. Doing so requires commitment. In countries where thelevel of electrification remains low (e.g., the Sahel countries, Figure 1.16), the question is how to deliver affordable andreliable service at scale. In countries approaching universal access (e.g., India, Peru), the question is how to connect
those hardest to reach.
The quantitative analysis above provides rich data for mapping the journey toward universal electricity access. But
data alone cannot chart the course over the next decade. It will be imperative to look beyond the data into the latest
innovations in policy and regulation, public and private investment, and business models for electrification. National
authorities and the international community have identified good practices. Their insights are summarized below.

INTEGRATED ELECTRIFICATION STRATEGIES AND PLANNING TO DRIVE POLICYMAKING AND INVESTMENT DECISIONS
The most successful national strategies integrate grid improvements, mini grids, and off-grid technologies—presenting
credible paths to universal access. As in Myanmar and Togo, the strategy must span the power sector value chain and all
population segments to support economic and social development goals. National ownership, coherence, inclusivity,
capacity, robustness, and data transparency/accessibility are key principles in developing effective initiatives to beundertaken by local authorities and their development partners.14 Comprehensive data from the Multi-Tier Frameworkand new electricity-access planning techniques (e.g., geospatial least-cost algorithms based on satellite imaging)and tools such as the Global Electrification Platform15 are critical for informed decision-making. Better quality andfewer gaps in data will make these tools more practical. These tools also need to capture more information about howelectricity is actually used so that communities can realize its full benefits.

POLICY FRAMEWORKS, WORKABLE REGULATIONS, AND STRONG
INSTITUTIONAL ARRANGEMENTS TO CREATE ENABLING ENVIRONMENTS
A quarter of the access-deficit countries now have comprehensive policies to improve access—the culmination ofa broader trend of steady policy improvements in those countries (ESMAP 2018). Yet regulatory frameworks that
support mini grids and off-grid systems have improved faster than those governing grid electrification. Most accessdeficit countries still have a way to go to make their utilities transparent, operationally efficient, and financially viable.
Many countries with the right policies and regulations struggle to implement, monitor, and enforce them. This isbecause power sector reform efforts are shaped by a country’s political and economic context and are more likely
to gain traction when led by champions enjoying broad stakeholder support. Also, reform efforts should be driven by
and tailored to desired policy outcomes, rather than attempting to follow a predetermined process. This warrants apluralism of approaches going forward (Foster and Rana 2019). Given the rapid evolution of mini grids and large offgrid sector growth, it is important to update enabling frameworks to capture the nuances of these new sectors. In the
instance of pay-as-you-go, the enabling policy and regulatory framework must go beyond the energy sector and also
cover aspects of digital development and financial inclusion. Fostering gender equality would help improve sector
governance and sustainability in industry practices (USAID 2018).

14
The Roundtable Initiative has embraced these principles. It also seeks to improve coordination among development partners and practitioners onenergy system modeling and planning in developing countries, based on a code of conduct aligned with the 2005 Paris Declaration on Aid Effectiveness(https://energyeconomicgrowth.org/publication/key-principles-improving-support-strategic-energy-planning-developing-and-emerging).
15

See https://electrifynow.energydata.info/.

CHAPTER 1 • Access to electricity

31

INNOVATIONS IN TECHNOLOGY AND BUSINESS MODELS TO REACH THE
REMAINING UNSERVED POPULATION
Encouraging rapid development of markets and promoting private sector participation (as Kenya and Nigeria havedone) is essential to drive down the cost of electrification and to ensure that efforts are consistent with consumers’
needs. New areas of private sector development include: (i) greater use of distributed renewable energy systems
as battery storage costs decline; (ii) high-efficiency appliances for residential and productive uses and in public
institutions; (iii) institutional and business delivery models tailored to poor, remote, fragile, and conflict-ridden countries(e.g., Haiti, Yemen); and (iv) digital technologies, such as the use of Internet of Things technologies, especially for offgrid households and micro, small, and medium enterprises, integrated with digital payment and financial services.
Technological and business model synergies between clean cooking and electrification (e.g., electric cooking, payas-you-go, and results-based financing) are also creating opportunities for integrated approaches that can grow themarket.

LEVERAGED PUBLIC AND PRIVATE FINANCING TO FUND ELECTRIFICATIONAT SCALE
Expanding access to electricity—especially for clean technologies like renewable energy mini grids and off-grid
electrification—remains underfunded, especially in Sub-Saharan Africa. Financing for off-grid electrification
represented just 1.2 percent of total funding for energy access in 2017. It is concentrated in a few countries; Kenya,
Tanzania, and Uganda account for more than half of this financing (SEforAll and CPI 2019). As public financing will
likely remain limited over the next few years, universal access will not be achieved by 2030 without unlocking private
financing. Available public resources are best spent on measures likely to attract private sector finance and on
extending access to populations living in areas unlikely to attract private financing, as well as on subsidizing service
for those who simply cannot afford it. Mini grid and off-grid solutions that are likely to serve much of the unelectrified
population (ESMAP 2019, IEA 2019c), are often considered high-risk investments by commercial financiers. Therefore,
one of the imperatives identified in the latest off-grid market trends report is to unlock financing from local commercial
banks (ESMAP 2020). So-called results-based financing—where flows are tied to delivery of services—ensures thatelectrification reaches the intended population. Further private efforts may depend on additional risk mitigation by
public authorities and new approaches to encourage local entrepreneurs and foster access to finance. Public resourcesin the form of credit lines, guarantees, and working capital facilities should be used to leverage the needed private
capital and mitigate risk.

LEAVING NO ONE BEHIND
Electrification strategies will succeed only when the technical elements cited above are combined with inclusive
approaches for electrifying remote populations. As universal access to electricity draws near, the unelectrified
population will be poorer and more rural, living in fragile regions affected by conflict and violence. Both demand andsupply subsidies will be required to reach these populations. They will have to be better targeted and designed toensure sustainability, minimize distortions, and enable (rather than displace) private-sector service delivery andfinancing. Energy safety nets integrated with social assistance programs could supply vulnerable households withaccess to essential services (SEforAll 2020).
It will be equally important to shift thinking about the humanitarian challenge of displaced people and host communities
toward development of solutions that address the effects of crises on local infrastructure and institutions (box 1.2).
Factors to consider when providing such households with energy services include increased awareness about cyclicalincomes (which make it hard to pay upfront connection costs), the lack of land titles, and the need for mobile energy
services (e.g., off-grid technology). In addition, access is not the same as use. It is therefore important to look at the link
between usage and affordability. Using appliances could boost livelihoods and incomes. Specific approaches suitablefor fragile and conflict-affected contexts include greater reliance on and collaboration with local government andbusinesses, nonprofit partners, and United Nations agencies.

32

Tracking SDG 7: The Energy Progress Report 2020

Access deficit, 2018 (million)
0

Annualized increase in access,2010 - 2018 (pp)Access rate, 2018 (%)

20

40

0

50

100

0

5

BOXCambodia
1.2 • PROVIDINGELECTRICITYTO RECORD NUMBERS
OFCambodia
FORCIBLY
Cambodia
1
92
DISPLACEDPEOPLE
Afghanistan
Afghanistan
Afghanistan 0.5
99
Kenya

Kenya

13

7

Kenya

75

10
8

7

Timor-Leste
Timor-Leste
0.2
Timor-Leste
Today,
forcible displacement
affects a record
number of 75 million 86
people aroundthe world, including6 almost

24 million
refugees
Of the75 million forciblyat theend of 2018,5about 20
Papua New
GuineaPapua New
GuineaPapua
New Guinea
4 and asylum seekers.
59 displaced people
million wererefugeesand over 3.5 million were
asylum seekers (UNHCR
2019).
Kiribati
Kiribati100
0.1
Solomon Islands

Solomon Islands

0.2

Kiribati

5

Solomon Islands

67

4
Historically, humanitarian and development actors do not provide access to electricity among
refugeeEswatini to do so, for a start.
Eswatini
77 Some host governments
Eswatini
4
0.3lack the expertise and funding
households.
They
are reluctant
to
43 are optimistically considered
UgandaUganda4authorize
long-term infrastructure
for refugeesettlements that
temporary.
Uganda25
Lesotho47

Lesotho1

Lesotho4South Sudan

3

Electricity
access for displaced populations
is now receiving growing attention, thoughreliable information and
Bangladesh
Bangladesh
Bangladesh
24
485
monitoring are scarce. The best globallyLao
comparable
data
presently
available
comefrom
the Integrated Refugee
People's
Lao People's
Lao People's 0.1
398
and Forcibly
System of the United NationsDemocratic
High Commissioner
for Refugees
Democratic Republic
Republic
Democratic
RepublicDisplaced Energy Information
100
3
Bhutan0.1
Bhutan(UNHCR).
The system
is a global monitoringBhutan
toolkit accessible at https://eis.unhcr.org/about.
South Sudan

South Sudan

8

28

Existing datashowsthat refugees have disproportionately
lower accessto grid electricity
than their 3surrounding
69
Congo
Congo
Congo
2
host communities. According to the UNHCR findings (Figure B1.2.1), the most striking cases were in Rwanda
94
3
Nepal
Nepal
Nepal
2
(Gihembe, Kigeme,
Mugombwa, Nyabiheke) and Tanzania (Nyarugusu), where just 10 percent of refugees had
335aRwanda with 25–37 percent in the host communities.
RwandaRwanda8
access to
the electricity
grid in 2018, comparedIn Cameroon
Mali 5 percent 51
Mali to the 3
Mali Kette,
9 Meiganga, Minawao), only
(Douala, Gbiti,of the refugees had accessgrid in 2018,29
Guinea-Bissau
Guinea-Bissaucomparedwith 25
communities. In Bangladesh,the gap between
the refugees3 in 10 camps
1 percent in the host Guinea-Bissau
CentralAfricanCentral Bazar
African and the host community
in Cox’s
wasAfrican
particularly stark:no refugees hadCentral
accessto grid power,
whereas3
32
3
Republic
Republic
Republic
up World
to 80average
percent of the host community
hadaccess.
In
othercountries,
including
Burkina
Faso(Gandafabou,
0.3
90World average
World average
4
Goudebo, Mentao), Chad (Aradib, Djabal, Goz Amer), and South Sudan (Doro, Ezo, Gendrassa, Kaya, Lasu, Yusuf
Batil), neither refugees nor the host communities had access, underlining the poverty of areas hosting refugees
in many countries.
FIGURE B1.2.1 • Percentage of refugee households having access to on-grid electricity in selected
communities
100%
90%

80%

80%
70%
60%
50%

37%

40%

25%

30%

25%

20%
10%

0%

0%

Bangladesh(2018)

Burkina Faso
(2018)

5%

1%
0%

Cameroon(2018)

Chad(2018)

10%
7%

10%

10%

0%

0%

Access rate of selected refugee camps

Kenya(2015)

Rwanda(2018)

Tanzania(2019)South Sudan(2019)

Access rate of host communities

Source: Integrated Refugee and Forcibly Displaced Energy Information System (https://eis.unhcr.org/home).

Limited data suggest that refugees do have somewhat better access to off-grid electricity. A study conductedamong 600 sample households in three refugee camps (Gihembe, Kigeme, Nyabiheke) in Rwanda in 2018 foundthat 41–51 percent of the refugees had access to electricity for lighting from an off-grid power source (Sandwell

CHAPTER 1 • Access to electricity

33

and others 2019).b Another study conducted among 500 sample households in Nyarugusu in Tanzania in2017 found a similar situation, with 43 percent of refugees having access through off-grid electricity (Rivoal
and Haselip 2017). This indicates the potential for market-based approaches to off-grid electricity solutions
in refugee settings. One estimate has refugees and internally displaced people spending USD 223 million on
off-grid lighting technologies alone, of which USD 121 million is attributed to refugees living in camps (Moving
Energy Initiative 2018).
In order to chart a strategy for achieving SDG 7, more work is needed to gauge the differences in access to anddemand for energy among refugees and hosts.
Source: Integrated Refugee and Forcibly Displaced Energy Information System (https://eis.unhcr.org/home).
a. The country data presented in this paragraph can be found at https://eis.unhcr.org/home.
b. On average across all three camps, 58 percent reported no access to electricity, while 41 percent reported either access to electricity
through solar lanterns (21 percent), solar home systems (16 percent), mini grids (2 percent), or rechargeable batteries (2 percent).

ENERGIZING WOMEN
Access to electricity plays a critical role in poverty reduction for women and girls. Women’s employment and leisure will
improve with increased access to electricity. Poor electricity supply was pinpointed as the biggest obstacle to growthby 25 percent of female-headed enterprises surveyed in Tanzania and 19 percent in Ghana. Statistical data from thesecountries show a positive relationship between the productive use of electricity and women’s economic empowerment.
Use of electrical appliances allowed for diversification in products for sale and helped female entrepreneurs attract
more customers (Wilson 2020). The provision of electric light amplifies time savings by increasing efficiency andadding flexibility in the scheduling of household tasks. Freeing up women’s time is a prerequisite for investments intheir education and life choices, encouraging them to seize economic opportunities and participate in economic,
political, and social life (World Bank 2012).
Electrification projects can promote gender equality in several ways. For example, ensuring that the upfront cost ofelectricity provision and electric appliances is affordable to women and women-led businesses—who are less likely
to have access to finance—would facilitate grid and off-grid connections and the use of energy services. Also, genderdisparities can be ameliorated with approaches that ensure women have the same opportunity as men to benefit from
improved income-generating activities. With a focus on closing gender gaps in employment and skills development,
projects can also address women’s underrepresentation in the energy sector workforce. IRENA’s online gender survey
from 2018 highlighted access to training and skills development programs. In fact, these were seen as a key measure
to improve women’s engagement in deploying renewables for energy access (IRENA 2019b).To ensure that gender isfactored into energy projects, specific actions throughout the project cycle are required: a gender-gap assessment, aplan of action for interventions, and a focus on monitoring and evaluation that tracks the narrowing of gender gaps.
An in-country example from Ethiopia—where the government has launched a reform of its energy sector to reach
universal electrification by 2025—aims to create more equitable institutions and equal benefits for women. A first-ofits-kind approach, the NEP and NEP 2.0 initiatives established new ways of looking at gender, focusing on constraints
in employment, child care, sexual harassment, female entrepreneurship, and consumer-level affordability (World Bank
2020).

GOING BEYOND CONNECTIONS: IMPROVING LIVELIHOODS AND HUMAN
CAPITAL
Electrification programs must be grounded in a broader agenda of social transformation. Countries with universal
electricity access built their programs as part of a transformative agenda of social and economic development (e.g.,
China, Tunisia, United States of America, Viet Nam). Electricity access programs should be designed to support
countries’ sustainable development initiatives. There is growing evidence that demand-side factors are impeding thescale-up of electrification, particularly in Sub-Saharan Africa, where electrified households often remain at minimum
consumption levels, not making full use of electricity’s socioeconomic benefits. Persistent lack of household demand,inability to pay, or unwillingness to pay makes service providers reluctant to serve low-income users and threatens

34

Tracking SDG 7: The Energy Progress Report 2020

the sustainability of efforts across all technologies—grid, mini grid, and off-grid. That so many rural schools and healthfacilities remain without reliable access to electricity (box 1.3) likewise limits the impact of electrification because theobjectives of human capital development remain unrealized.
Well-targeted demand-side interventions can unlock the potential of electrification and lead to broader social andeconomic development effects. Programs that emphasize productive uses of electricity, raise awareness, increase theavailability and affordability of energy-efficient appliances, provide financial support, and offer extension services forthe development of enterprises or better farming can scale up the consumption of electricity and stimulate a virtuous
circle of productive use. In Bangladesh, the government-owned Infrastructure Development Company Limited launched
intensive customer-awareness campaigns to address load-uptake challenges in mini grids. The campaigns brought in
new customers and raised electricity utilization. Furthermore, the range of off-grid solutions to promote productive
uses of solar energy, such as solar water pumps, cold storage, and solar milling, as well as products servicing public
institutions, is rapidly expanding, with a market of USD 11.3 billion in 2018 in Sub-Saharan Africa alone (Lighting Global2019).

BOX 1.3 • SUPPORTING OTHER SDGS BY SUPPLYING POWER TO EDUCATIONFACILITIES AND HEALTH CENTERS
Providing electricity to schools and health centers offers broad benefits that will assist in reaching objectives
codified in a range of SDGs, most directly SDG 3 (health) and 4 (education) but also SDG 5 (gender) and SDG 8(work and economic growth). The MTF team collected information from public institutions including health andeducation facilities as a part of the household survey.a
Education facilitiesb
In 2018, the Multi-Tier Framework (MTF) survey compiled data in public institutions in Cambodia, Ethiopia, Kenya,
Myanmar, Nepal, and Niger. The data were collected at the facility level by interviewing officers best positioned torespond at the institutions.
In the surveyed countries, 31 percent of educational facilities are electrified through an on-grid source of electricity
and 9 percent through off-grid systems; 60 percent have no access to electricity.
The national public grid is the primary source of electricity for educational facilities with access to power. Morespecifically, 49 percent of schools in Nepal are electrified through the public grid, 72 percent in Kenya, and only 22
percent in Ethiopia. An exception to this trend is Niger, where solar energy sources, including solar home/lighting
systems, mini grids, and batteries, are primary providers of electricity for 3 percent of schools. Education facilities
also rely on solar as backup power to cover urgent energy demand. This is the case for 86 percent of facilities in
Cambodia and 15 percent of schools in Kenya.
FIGURE B1.3.1 • Electrification of schools in selected MTF countries, by source
Access to electricity by source (%)

100
90

70

50

30
20
10
0

41

7

58

60

40

21

34

80

71
23

10

43

49

92

10
32

Cambodia72
722
Myanmar

Nepal

Kenya

Off-grid %On-grid %Ethiopia

3
5
Niger

No electricity %ss to electricity by source (%)

Schools and other educational facilities use electricity for lighting (72 percent), computers and printers (36percent), and fans or evaporative air-cooling systems (32 percent). A lack of electricity to power appliances,100
however, is a major
40 percent of educational facilities.
This is especially true for schools in Myanmar
11 constraint for10
10
19

90
80
70

CHAPTER 60
1 • Access to electricity

50

13

41

28

25

35

66

50

25

40
30

77
56

51

(56 percent) and Cambodia (28 percent). Other relevant obstacles are the lack of appliances in the market andthe high cost of electric-powered items, which reduces the full benefits of access to electricity.

Access to electricity by source (%)

Beyond access, the poor quality of electricity service affects the functioning of educational facilities. At theaggregate level, only 16 percent of schools report enjoying 24 hours of electricity each day. Unscheduledinterruptions hinder the functioning of more than 25 percent of educational centers. About 28 percent of schools
report damage
to equipment from frequent voltage fluctuations.
100
90c
Health centers

21

34

80

41

7

58
The covid-19
pandemic
highlights the need for reliable and affordable electricity to health centers. MTF collected
70
71
data across
60 730 health centers, including clinics and hospitals in Cambodia, Ethiopia, Kenya, Myanmar, Nepal,
23
1092
and Niger.
50
40

10countries, around 75 percent of health facilities72
Across the surveyedhave access to a primary source of electricity
30(42 percent
through grid access, 33 percent throughoff-grid
solutions),
while 25 percent
remain unelectrified.
7
49
43
20
These aggregate
results
mask large
discrepancies at the country level, as well as quality and reliability of supply.
32
In Kenya,1077 percent of health centers rely on the public national grid to cover their22
primary electricity
needs. At
3
5 electricity
the same0time, 66 percent of health centers in Cambodia use off-grid solutions to cover their primary
MyanmarKenya
Niger
demand, and 83Cambodia
percent of them use
solar systemsNepal
as a backup powersource. Ethiopia
Off-grid %On-grid %No electricity %FIGURE B1.3.2 • Electrification of health institutions in selected MTF countries, by source

Access to electricity by source (%)

100
90

11

10

19

80
70
60

50

10
13

41

25

66

50

25

40

56
40

20

0

51

77

30

10

28

34

24
Cambodia

Myanmar
On-grid %Nepal
Off-grid %Kenya

Ethiopia

21
Niger

No electricity %The health centers use electricity mainly for lighting (57 percent), refrigerators for vaccines (40 percent), andfans or evaporative air-cooling systems (28 percent). They also reported, however, that the use of electricpowered medical appliances is limited owing to no availability, high cost, and insufficient energy.
In every country analyzed, the power supply is compromised by unscheduled interruptions and voltage
fluctuations. Twenty-five percent of health facilities reported that unscheduled outages affect the capacity
to deliver essential health services. Damage to equipment caused by poor-quality connections and frequent
voltage fluctuations are also constraints for 28 percent of health centers.
The electrification of educational and health centers should be designed to promote their long-termsustainability. Advances in off-grid electrification—including remote monitoring and private sector delivery—
could be important elements of sustainability. It is possible that even off-grid facilities are being overlooked whileplanning grid expansion. The cost of extending access is high, but the cost of continued lack of electricity accessis higher (UN DESA 2014).
a Within the selected human settlement areas or enumeration areas, field teams identified all public institutions that households in thecommunity could reach out to. Then, the field teams interviewed all (or largest) public institutions identified within and nearby the community.
b The sample of education facilities include data from 179 facilities in Cambodia, 217 in Myanmar, 368 in Nepal, 482 in Kenya, 221 in Ethiopia
and 92 in Niger. Definition of education facilities include primary, secondary, vocational/technical schools and universities.
c The sample of health facilities include data from 25 facilities in Cambodia, 67 in Myanmar, 282 in Nepal, 153 in Kenya, 180 in Ethiopia and 23
in Niger. Definition of health facilities include health centers, private clinics, hospitals and referral hospitals.
Source: Multi-Tier Framework, World Bank (https://mtfenergyaccess.esmap.org/).

36

Tracking SDG 7: The Energy Progress Report 2020

METHODOLOGYDATABASE
The World Bank’s Global Electrification Database (https://databank.worldbank.org/source/world-developmentindicators) compiles nationally representative household survey data as well as census data from 1990 to 2018. It also
incorporates data from the Socio-Economic Database for Latin America and the Caribbean, the Middle East and North
Africa Poverty Database, and the Europe and Central Asia Poverty Database, all of which are based on similar surveys.
At the time of this analysis, the Global Electrification Database contained 1,133 surveys from 144 countries, excluding
surveys from high-income countries as classified by the United Nations. In general, about 25 percent of the countries
publish or update their electricity data each year, thus permitting global data collection since 2010. Greater investment
in data collection and capacity building is needed in order to gain a more comprehensive and accurate understandingof the electricity access picture (chapter 6).

ESTIMATING MISSING VALUES
Surveys are typically published every two to three years, but they can be irregular and infrequent in many regions.
To estimate values, a multilevel, nonparametric modeling approach developed by the World Health Organization toestimate clean fuel usage was adapted to predict electricity access and used to fill in the missing data points for thetime period between 1990 and 2018. Where data are available, access estimates are weighted by population. Multilevelnonparametric modeling takes into account the hierarchical structure of data (country and regional levels), using theregional classification of the United Nations.
The model is applied for all countries with at least one data point. In order to use as much real data as possible, results
based on real survey data are reported in their original form for all years available. The statistical model is used to fillin data only for years where they are missing and to conduct global and regional analyses. In the absence of survey
data for a given year, information from regional trends was borrowed. The difference between real data points andestimated values is clearly identified in the database.
Countries considered “developed” by the United Nations and classified as high-income are assumed to haveelectrification rates of 100 percent from the first year the country joined the category.
In the present report, to avoid having electrification trends from 1990 to 2010 overshadow efforts since 2010, themodel was run twice:With survey data + assumptions from 1990 to 2018 for model estimates from 1990 to 2018

With survey data + assumptions from 2010 to 2018 for model estimates from 2010 to 2018

MEASURING ACCESS TO ELECTRICITY THROUGH OFF-GRID SOURCESGOGLA Global Off-Grid Solar Market Database 2020 is updated through a semi-annual data collection run in partnershipwith the World Bank Group’s Lighting Global program and the Efficiency for Access Coalition. The database contains
sales volumes of off-grid solar lighting products that include at least one light point, a panel, and a battery, excluding
products sold as components. Sales volumes are collected for every country in the world; however, data on a specificcountry are included only when it has satisfied the three-data-point rule. This means that at least three separate
product manufacturers need to have reported sales for any single data point to be reflected in the figures throughout
the report. Where there are fewer than three responses for a region, country, or product category, no results are shown
to protect the proprietary interests of the companies that have supplied data in support of this industry report. Moreinformation can be found at https://www.gogla.org/global-off-grid-solar-market-report.

CHAPTER 1 • Access to electricity

37

IRENA’s 2018 off-grid database builds on GOGLA’s data, adding mini grid data, data from national rural electrification
programs, and data from international development projects, commercial vendors, and nongovernmentalorganizations. The database covers only developing countries. Its data are obtained from large databases (e.g., GOGLA
and government agency websites and reports) as well as websites of other agencies and institutions active in the offgrid sector. During the merging of data from these different sources, care is taken not to double count the observations
from different sources and to ensure that planned projects and programs have been implemented. To account for thelimited lifetime of small solar devices, the number of lights sold or distributed in the last three years is taken as thecurrent number of these devices in operation. It is assumed that solar home systems last for five years (i.e., a five-year
total is used) unless there is evidence that a long-term maintenance and replacement program is in place. More detailsof the methodology used to compile this data can be found in IRENA (2018).
The tier-wise data are presented by technology as:Below Tier 1: Lighting (<11W)Tier 1: Small solar home systems (11–50W); large solar home systems (>50W); small PV mini grid access

Tier 2+: Larger PV mini grid access and non-PV mini grids.

In the GOGLA database, the tier-wise data are calculated differently than highlighted above. Tier 1 includes systems
with a wattage of less than 11W and multiple lights; Tier 2+ includes solar home systems with a wattage greater than
40W. A reconciliation of the different tier-wise methodologies will be attempted in future reports.

CALCULATING THE ANNUAL CHANGE IN ACCESS
The annual change in access is calculated as the difference between the access rate in year 2 and the rate in year 1,
divided by the number of years to annualize the value:(Access Rate Year 2 – Access Rate Year 1) / (Year 2 – Year 1)
This approach takes population growth into account by working with the final national access rates.

COMPARING THE ELECTRIFICATION DATA METHODS OF THE WORLD BANK AND
THE IEA
The World Bank and IEA maintain separate databases of global electricity access rates. The World Bank’s Global
Electrification Database derives estimates from a suite of standardized household surveys and censuses that are
conducted in most countries every two to three years, in conjunction with a multilevel nonparametric model used to
extrapolate data for the missing years. This ensures that demand-side data are being collected. The IEA Energy Access
Database sources data, where possible, from government-reported values for household electrification (usually basedon utility connections), which focuses more on supply-side electrification data. IEA considers a household to haveaccess if it receives enough electricity to power a basic bundle of energy services (IEA 2019a, 2019c). The World Bankutilizes a similar access structure to determine energy access called the Multi-Tier Framework, ranging in a tiered
spectrum, from Tier 0 (no access) to Tier 5 (highest level of access).
These two different approaches can sometimes lead to differing estimates. Access levels based on household surveys
are moderately higher than those based on energy sector data because they capture a wider range of phenomena,
including off-grid access, informality, and self-supply systems.
A comparison of the two datasets in the previous edition of this report (and updated in this edition) highlights
their different strengths. Household surveys, typically conducted by national statistical agencies, offer two distinct
advantages for measures of electrification. First, with longstanding efforts internationally to harmonize questionnaire
designs, electrification questions are mostly standardized across country surveys. Although not all surveys reveal
detailed information on the forms of access, survey questionnaire designs can now capture emerging phenomena
such as off-grid solar access. Second, data from surveys convey user-centric perspectives on electrification. Survey
data capture all forms of electricity access, painting a more complete picture of access than may be possible fromservice provider data.

38

Tracking SDG 7: The Energy Progress Report 2020

Government data on electrification reported by national ministries of energy take the form of supply-side data on
utility connections. Although not published by every government, these kinds of data offer two principal advantages
over national surveys. First, administrative data are often available on an annual basis and, for this reason, may be
more up to date than surveys, which are updated only every two to three years. Second, administrative data are notsubject to the challenges that can arise when implementing surveys in the field. Household surveys (particularly thosetaken in remote and rural areas) may suffer from sampling errors that may lead to underestimates of the access deficit.

CHAPTER 1 • Access to electricity

39

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https://www.worldbank.org/en/news/feature/2020/02/03/ethiopia-broadens-opportunities-for-womenin-the-energy-sector.
World Bank and IEA (International Energy Agency). 2015. Progress Toward Sustainable Energy: Global Tracking
Framework Report. World Bank: Washington, DC. DOI: 10.1596/978-1-4648- 0690-2. http://trackingenergy4all.
worldbank.org/.

CHAPTER 1 • Access to electricity

41

CHAPTER 2ACCESS TO
CLEAN FUELS ANDTECHNOLOGIESFOR COOKING

Photo: A woman cooks indoors with an ethanol-fueled cooking stove/Getty Images

CHAPTER 2: ACCESSTO CLEAN FUELS ANDTECHNOLOGIESFOR COOKING

MAIN MESSAGESStatus of access: In 2018, 63 percent (56–68 percent16) of the global population had access to clean cooking
fuels and technologies; the global population without access was 2.8 billion (2.4–3.3) people. Without prompt
action, universal access will fall short of SDG goals by almost 30 percent. Meanwhile, exposure to household
air pollution will continue to contribute to millions of deaths from noncommunicable diseases (including heartdisease, stroke, and cancer) and pneumonia. Household air pollution will continue to worsen climate change.

Access and the 2030 target: The annual rate of access to clean cooking fuels and technologies from 2010 to2018 increased by less than one percentage point (pp) as population growth outpaced the number of those withaccess. In the decade leading up to 2030, increases in excess of 3pp per year are required to achieve the goal ofuniversal access to clean fuels and technologies by 2030.



Regional highlights: Greater access to clean cooking was achieved largely in two regions of Asia. From 2010 to2018, Eastern Asia and South-eastern Asia saw annualized increases in access of 1.6pp—while the numbers ofpeople lacking access fell from 1.0 billion (0.8–1.2) to 0.8 billion (0.5–1.1). Central Asia and Southern Asia also saw
improved access to clean cooking, with annualized increases of 1.5pp. The 1.11 billion (0.9–1.3) people without
access dropped to 1.0 (0.7–1.3) billion. In Sub-Saharan Africa, meanwhile, a stagnant access rate (annualized
increase of 0.4pp) combined with rapid population growth have meant that the numbers of people without accesshave risen from 750 million (730–750) people to 890 million (870–910) people.

Urban-rural divide: There are urban-rural discrepancies worldwide in access to clean cooking fuels andtechnologies: 83 percent of urban dwellers have access to clean fuels and technologies, compared with 37 percentof those living in the countryside. These discrepancies have been shrinking since 2010 owing, first, to increased
access in rural areas, and, second, to population growth in the cities that is beginning to outpace access.



The top 20 countries with access deficits: From 2014 to 2018, 20 countries accounted for more than 80
percent of the global population without access to clean cooking fuel.17 In terms of the percentage of the national
population lacking access, 19 of the 20 countries with the lowest percentage of the population having access wereleast-developed countries in Africa. Of these, 15 had annualized increases in access over the same period of lessthan 0.1pp, with some of these displaying potential decreases in access.

Fuel trends: In low- and middle-income countries of Central Asia and Southern Asia, Eastern and South-eastern
Asia, Latin America and the Caribbean, Oceania, Sub-Saharan Africa, and Western Asia and Northern Africa, theuse of gaseous fuels (liquefied petroleum gas [LPG], natural gas, and biogas) continues to increase. Since 2010,
gas has overtaken unprocessed biomass fuels as the dominant fuel worldwide. (Unprocessed biomass, charcoal,coal, and kerosene are considered polluting fuels.) In urban areas, the use of electricity for cooking has risen, but
gas remains the most common fuel. In rural areas, meanwhile, a decline in the use of polluting fuel, particularly
raw coal, has been accompanied by increased use of gas, though unprocessed biomass fuels remain dominant.
Finally, the global proportion using charcoal is low, but charcoal has overtaken unprocessed biomass in SubSaharan cities.

16
Parenthetical figures appearing after estimates throughout the chapter are 95 percent uncertainty intervals, as defined in the methodology section at the end of this chapter.
17
The top 20 access-deficit countries are the 20 countries with the highest access-deficit population. Among them are Afghanistan, Bangladesh,
China, Democratic People’s Republic of Korea, Democratic Republic of Congo, Ethiopia, Ghana, India, Indonesia, Kenya, Madagascar, Mozambique,
Myanmar, Nigeria, Pakistan, Philippines, Sudan, Uganda, United Republic of Tanzania, and Viet Nam.

43



Survey harmonization: Current data collection on household fuel use from national surveys offers a clear pictureof access to clean cooking. Historically, however, these surveys typically ask only about the primary cooking fuel,eliciting little information on secondary household stoves or sources of air pollution (i.e., fuels and technologies
used for lighting and heating). Improved survey questions regarding household fuel use will allow for a fuller
understanding of the health, climate, and social impacts of household energy use, and attributes leading to moresustained adoption of clean cooking.



Outlook: Since 2010, only small improvements in access to clean fuels and technologies for cooking have beenrealized. Although Asia has made notable gains, stagnant growth in access, combined with rapid population
growth, have brought progress in Sub-Saharan Africa to a standstill. If this trend continues, any hope of achieving
universal access rates by 2030 will be quashed, leaving a third of the global population vulnerable not only toadverse health effects but also to social and economic disadvantages. The latter is especially true for women andchildren, who shoulder time-consuming household tasks of gathering fuel and tending smoky stoves. These tasks
take them away from remunerative work on the one hand while on the other subject them to adverse environmental
conditions. That said, universal access remains achievable if serious efforts were made toward accelerating thetransition to clean cooking worldwide, and particularly in Sub-Saharan Africa.

44

Tracking SDG 7: The Energy Progress Report 2020

ARE WE ON TRACK?

I

n 2018, 63 percent (56–68) of the global population had access to clean cooking fuels and technologies, comprising
electric, liquefied petroleum gas (LPG), natural gas, biogas, solar, and alcohol-fuel stoves. (Technical recommendations
defining what can be considered “clean” fuels and technologies are set out in WHO guidelines for indoor air quality:
household fuel combustion (WHO 2014). Yet there remain some 2. 8 billion (2.4, 3.3) people who rely on polluting
fuels and technologies for cooking, including traditional stoves paired with charcoal, coal, crop waste, dung, kerosene,
and wood. Due to limitations in the underlying data, analyses use types of cooking fuel rather than cookstove and fuelcombinations. (The methodology section at the end of the chapter provides additional details.)
Global access is tracked by surveying proportions of the population that rely primarily on clean cooking fuels andtechnologies. The global access rate has been improving over the past few decades, albeit slowly (Figure 2.1).18 By
2030, if trends continue, only around 70 percent of the population worldwide will have access to clean cooking fuels
and technologies (IEA 2019).This means nearly a third of the global population will be exposed to harmful household
air pollution from cooking with polluting fuels and devices, and many will still devote huge amounts of time to gathering
fuel instead of on remunerative work, schooling, and other productive or leisure activities.
FIGURE 2.1 • The global population with access to clean cooking (in percentages)

Population with access to clean fuels andtechnologies for cooking (SDG 7.1.2)

100%

75%

63%
56%

50%

25%

0%
2000

2005

2010

2015

Labels represent access-rate point estimates for 2010 (left) and 2018 (right)
Source: WHO.
Note: The estimates published this year rely on statistical modeling and are in accordance with previous estimates published within the confidence
intervals. Progress through 2018 was estimated by modeling survey data and UN population estimates (see methodology section at the end of thechapter).

1

6000

0.75

Population (millions)

8000

ercentage of global population with access to clean
fuels and technologies for cooking

SDG = Sustainable Development Goal.

18
Except as otherwise indicated, the data underlying the figures in this chapter were drawn in January 2020 from WHO’s Household Energy Database, https://www.who.int/airpollution/data/household-energy-database/en/.
4000
0.5

45

CHAPTER 2 • Access to clean fuels and technologies for cooking

2000

0.25

FIGURE 2.2 • Regional populations, by rate of access to clean cooking fuels and technologies, 2018

Source: WHO.

Deficient access rates dominate in the developing countries of Sub-Saharan Africa and Asia (figure 2.2). Whenconsidering the average access-deficit for the five-year period between 2014 and 2018, the 20 countries with thelargest populations lacking access to clean fuels and technologies are concentrated in these regions (Figure 2.3).
FIGURE 2.3 • Top 20 access-deficit countries, 2014–18

Source: WHO.

46

Tracking SDG 7: The Energy Progress Report 2020

Between 2010 and 2018, the regions with the greatest progress in access to clean cooking were Eastern Asia andSouth-eastern Asia, with annualized increases of 1.6pp, and Central Asia and Southern Asia, with annualized increasesof 1.5pp. In Sub-Saharan Africa, however, the access rate was stagnant, with annualized increases of only 0.4pp overthis period.
Over the five-year period from 2014 to 2018, rural areas in Latin America, Central Asia and Southern Asia, and Eastern
Asia and South-eastern Asia broadly benefited from modest increases in the access rate (Figure 2.4). Meanwhile, Latin
American cities saw little change. Urban areas in many Asian countries displayed slower increases in access than theirrural counterparts. With a few exceptions, most countries in Sub-Saharan Africa saw little change in rural areas, while
country performance in urban areas showed a clear split between countries that improved access over this period andthose that did not.
FIGURE 2.4 • Average annual increase (percentage points) in the clean cooking access rate, by urban/ruralclassification, over the period 2014–18

Source: WHO.
pp = percentage points.

CHAPTER 2 • Access to clean fuels and technologies for cooking

47

100%

Population with access to clean fuels andtechnologies for cooking (SDG 7.1.2)

LOOKING BEYOND THE MAIN INDICATORS
75%

ACCESS AND POPULATION

63%
56%

50%

The global access rate to clean cooking fuels and technologies reached 63 percent (56–68) in 2018. As seen in Figure
2.5, the access rate has been steadily rising between 2000 and 2018, with an annualized increase in access to clean
cooking of 0.8pp (–0.2, 1.7) between 2010 and 2018. As shown in Figure 2.6, progress in access has decelerated since2012, dropping from just below 0.8pp per year between 2000 and 2015 to 0.7pp from 2017 to 2018. Even discounting
25%
potential slowing of progress, such increases are not enough to reach SDG target 7.1.2 by 2030. Moreover, as seen inprevious years, population growth continues to outpace the annual increase in the number of people with access toclean fuel and technologies in Sub-Saharan Africa: Figure 2.7 shows the annualized increase in the number of people
with access to clean fuels and technologies (orange), compared to the annualized population increase (green), by
0% the period 2014–18.
region, over
2000

2005

2010

2015

Over this period, population growth in Sub-Saharan Africa outstripped growth in the number of people with access toclean cooking—by around 18 million people each year. Thus, in this region 894 million (874–911) people, or around 85
percent of the population, lack access to clean fuels and technologies for cooking.

8000

1

6000

0.75

4000

0.5

2000

0.25

0

Percentage of global population with access to clean
fuels and technologies for cooking

Population (millions)

FIGURE 2.5 • Change over time in the absolute number of people (left axis) and percentage of the global
population (right axis) with access to clean cooking

0
2000

2005
Population without access2010
Population with access2015
Population percentage

Source: WHO.

As a result, in 2018, around 3 billion people lacked access to clean fuels and technologies for cooking. Furthermore, if
trends continue without changes in policy, the access deficit will shrink from 2.8 to 2.7 billion people (2.0–3.5) by 2030,
about half of them in Sub-Saharan Africa and a quarter of them in Central Asia and Southern Asia. Using IEA’s Stated
Policies Scenario, 2.3 billion people will still lack access in 2030 under current and planned policies (IEA 2019). Action
is urgently needed.

48

Tracking SDG 7: The Energy Progress Report 2020

Annualincrease
access
clean
fuels
and
technologies
Annualincrease
inin
access
toto
clean
fuels
and
technologies(percentage
points)(percentage
points)FIGURE 2.6 • Average annual increase (percentage points) in the global clean cooking access rate (thepercentage of people with access)

0.8
0.8

0.6
0.6

0.4
0.4 2000
2000

2005
2005

2010
2010

2015
2015

Source: WHO.

In 2010, we estimated that average annual increases of 2pp would be necessary to achieve the goal of universal accessto clean cooking. To make up for lax progress over the period 2010–18, however, the necessary annual increases inaccess rate now exceeds 3pp, nearly four times higher than the 0.8pp seen in the period 2010–18. The longer only
marginal improvements are made, the more challenging the goal of universal access by 2030.
FIGURE 2.7 • Annualized increase in population and in the number of people with access to clean cooking
over the period 2014–18, by region

World
World

109.9
109.9

83.1
83.1
8.8
8.8
8.7
8.7

Western Asia andWestern
Asia
andNorthern
AfricaNorthern Africa

8.5
8.5

Sub-Saharan Africa
Sub-Saharan Africa

Eastern Asia andEastern AsiaAsia
andSouth-easternSouth-eastern Asia

26.7
26.7
41.5
41.5

13.4
13.4

Central Asia andCentralAsiaAsia
andSouthern
Southern Asia

42.3
42.3

23.9
23.9
0
0

20
20

40
40

60
60
Population (millions)
Population (millions)

Annualized increase in population with access to clean cooking, 2014-2018
Annualized increase in population with access to clean cooking, 2014-2018

80
80

100
100

120
120

Annuliazed increase in population, 2014-2018
Annuliazed increase in population, 2014-2018

Source: WHO; UN population estimates.

CHAPTER 2 • Access to clean fuels and technologies for cooking

49

THE ACCESS DEFICIT
While the human cost from polluting cooking is gradually easing in most regions, the trend is being overtaken byalarming population increases in Sub-Saharan Africa: On a global scale, gains in the percentage of population having
access to clean cooking have been matched by population growth. These developments have caused a decades-longstagnation in the numbers of people without access to clean cooking, referred to here as the “access deficit.” Estimatessuggest this number has hardly deviated from 3 billion people in any year since 2000, as illustrated in Figure 2.1, withthe 2018 estimate of 2.8 billion people (2.4, 3.3) being equal to the 1990 value of 2.8 billion people (2.4, 3.1).
Stagnation in the global access deficit disguises key regional trends. As illustrated in Figure 2.8, the access deficit has
decreased consistently in Eastern and South-eastern Asia since 2000 and in the regions of Central Asia and Southern
Asia since 2010. In Sub-Saharan Africa, meanwhile, the access deficit is growing and has risen by around a factor of 50
percent since 2000.
FIGURE 2.8 • Access deficits by region (population without access to clean fuels and technologies),
2000–18

Population without access to clean fuels and technologies (millions)

1200

Central Asia and Southern
Asia
Sub-Saharan Africa

900

Eastern Asia andSouth-eastern Asia
Latin America and the
Caribbean

600

Western Asia and Northern
AfricaNorthern America andEurope300
Oceania excluding Australia
and New ZealandAustralia and New Zealand
0
2000

2005

2010

2015

Source: WHO.

2000

6%
19%

50

37%

38%

2010

2018

5%

5%

25%

37%

33%

36%

32%

Tracking SDG 7: The Energy Progress Report 2020

27%

2000

2005

2010

2015

FIGURE 2.9 • Proportion of the total global access deficit in the three largest deficit regions and the rest of
the world, 2000, 2010, and 2018
2000

6%
19%

37%

2018

5%

5%

25%

38%

Central Asia and Southern Asia

2010

37%

33%

Eastern Asia and South-eastern Asia

36%

32%

27%

Sub-Saharan Africa

Rest of the world

Source: WHO.

As illustrated in Figure 2.9, from 2000 to 2018, the proportion of the global access-deficit population residing in Central
Asia and Southern Asia has shown minimal change, remaining at just over a third lacking access. But the proportion living
in Sub-Saharan Africa has increased from approximately one-fifth to one-third of the total; meanwhile, the proportion
residing in Eastern Asia and South-eastern Asia has decreased 11 percentage points. As a result, in 2018 more people
without access to clean fuels and technologies reside in Sub-Saharan Africa than in Eastern Asia and South-eastern
Asia. If observed trends in access and population continue, it can be estimated that in 2030 Sub-Saharan Africa will
have the greatest access deficit, at around 44 percent of the region’s total population. This represents a substantial
geographic redistribution of the global access deficit and associated health, economic, and societal burdens. Future
policies should take these trends into account.

ANALYSIS OF THE TOP 20 ACCESS-DEFICIT COUNTRIESThe top 20 access-deficit countries (Figure 2.10) accounted for 82 percent of the global population (2014–18 average)
lacking access to clean cooking.19 India alone still accounts for the largest share of the access deficit at 25 percent,followed by China at 19 percent.
Six out of the 20 countries have proportions of their respective populations with access to clean fuels less than or equal
to 5 percent, including Democratic Republic of Congo, Ethiopia, Madagascar, Mozambique, Uganda, and Tanzania.
Seventeen out of the 20 countries have access rates under 50 percent.
The 20 countries with the lowest access rates have shown little to no sign of improvement, represented by near-zeroannualized increases (2014–18). Rapid annual gains in access (more than 2 percentage points) can, however, be seen
in several countries between 2014 and 2018, including Indonesia (4.3 points), Myanmar (2.4 points), Afghanistan (2.2
points), Congo, and Sudan (both at 2.1 points, see Figure 2.13).

19
The top 20 access-deficit countries are the 20 countries with the highest access-deficit populations. These are Afghanistan, Bangladesh, China,
Democratic People’s Republic of Korea, Democratic Republic of Congo, Ethiopia, Ghana, India, Indonesia, Kenya, Madagascar, Mozambique, Myanmar,
Nigeria, Pakistan, Philippines, Sudan, Uganda, United Republic of Tanzania, and Viet Nam.

CHAPTER 2 • Access to clean fuels and technologies for cooking

51

FIGURE 2.10 • The 20 countries with the largest populations lacking access to clean fuels and technologies,
2014–18 average
Access deficit (millions)
0

200

400

Annualized increase (pp)Access rate (%)

600

800

0

20

40

727

India

60

Nigeria

173

Bangladesh

130

Pakistan

113
5
4

1.8
1.1
0.5
0.0

74

71

58
44
41

Myanmar

41

Viet Nam

37

Mozambique

28

Madagascar

25

Afghanistan

24

Democratic People's
Republic of Korea
Ghana

23
21

Sudan

21

4.3

44

54

4.5

1.6
42

98

3.5

2.0

20

76

Kenya

2.5

1.3

7

Ethiopia

Uganda1.5

61

Democratic Republicof the Congo
Indonesia
Philippines
United Republicof Tanzania

0.5

45

544

China

-0.5

1.2

3

0.2
10

0.4

1

-0.1
23

2.4
61

1.6

4

0.2

1

0.0
32

2.3

10

0.6
24

1.5
46

2.1

Source: WHO.
rate (%)
increase (pp)deficit (millions)
FIGURE 2.11 • The 20Accesscountries
with the largest access Accessdeficits
to clean cooking, Annualized
2014–18
0

20

40

Access to clean cooking (2014-2018 average)

25
Pakistan
20

Mali

18

Malawi

18

Chad

8%

14

Kenya

Somalia

14

Guinea

12

1

3.8

Sudan

-0.1
2.5

Ghana

1%

Central African
Republic
Gambia5
Madagascar
2

Guinea-Bissau

2
Uganda

0.1

1

-0.1
0.1

3.4

0.2

2.6
0.1

1.2

2

0.0

0.3

0.1

0.9
0.0

0.5

0.0

0.7

0.0

0.5

0.0

0.6

4

-0.1

2.2

0.0
0.2

3.0
1

2

0.3

0.0
2.2

Bangladesh

0.2

0.2
Population without accessto clean fuels and
0.0 technologies for cooking(100
0.2million)

Maynmar
1.1

1.5

Sao Tome and0
Principe
Kiribati 0 000.0
Indonesia

1.0
Afghanistan

Nigeria

Liberia

-0.1

4

2.6

Democratic People's Republic of Korea

2%

-1

3

0.8

7
United Republic of Tanzania
5

Sierra Leone

2

India

Democratic
Republic 12 Ethiopia
South Sudanof the Congo
Rwanda12
Mozambique
Burundi
10

4%

0.5%

0

Philippines
41

Niger

16%

80

Viet Nam
54

Madagascar

32%

60

China
76

Democratic Republicof the Congo
United Republicof Tanzania
64%
Uganda

4
4.2

3

0.1

5

Annualized increase in access to clean cooking (2014 - 2018, pp)
Low income

Lower middle income

Upper middle income

Source: WHO.
pp = percentage points.
Access deficit (millions)
0

52

200

600

173

Annualized increase (pp)Access rate (%)
800

0

25

727

India
Nigeria

400

50

45
7

75

0.0
1.0 7: The
2.0Energy3.0
4.0
Tracking
SDG
Progress
Report5.0
2020

2.0
1.6

Madagascar

25

Afghanistan

24

Democratic People's
Republic of Korea
Ghana

23
21

Sudan

21

1

0.0
32

2.3

10

0.6
24

1.5
46

2.1

FIGURE 2.12 • The 20 countries with lowest percentage of the population with access to clean fuels andtechnologies, 2014–18 average
Access rate (%)

Access deficit (millions)
0

20

40

Democratic Republicof the Congo
United Republicof Tanzania
Uganda

60

80

0

1

2

Annualized increase (pp)
3

76
54
41

Niger

20

Mali

18

Malawi

18

Chad

14

Somalia

14

Guinea12South Sudan

12

Rwanda12

Burundi

10

3.8

0.0

0

0.1

0.2

0.3

0.2

0.8

-0.1
0.0

1.0

0.2

2.5
0.0

1.1
-0.1

2.2

0.1

3.4

0.2

2.6
0.1

1.2
0.0

0.3

0.1

0.9
0.0

0.5

Sierra Leone7

0.7

Liberia5

0.5Central African
Republic
Gambia5

0.6

2Guinea-Bissau2

Sao Tome andPrincipe
Kiribati

0
0

-0.1

2.6

25

Madagascar

4

0.0
0.0
0.0
-0.1

2.2

0.0

1.5

0.2

3.0
4.2

0.1

Source: WHO.
pp = percentage points.

Overall, in the 20 countries with lowest percentages of the population having access to clean fuels and technologies(Figure 2.12), the annualized access increase between 2014 and 2018 was small (always less than 0.3 percent);
data suggests that a few countries experienced decreases in access to clean cooking fuels during the same period.
These 20 countries are all least-developed countries and, with the exception of Kiribati, are all in Africa, highlighting
the increasingly important need to address access deficits in Africa. Figure 2.13 shows the 20 countries with thefastest annualized increase (2014–18) in access to clean cooking. Despite relatively steep increases in access, thepopulation lacking access is still significant in some of the larger countries. These countries with the largest deficits
also receive disproportionately limited financing (SEforAll 2019) and thus face challenges for scaling up clean fuels
and technologies.

CHAPTER 2 • Access to clean fuels and technologies for cooking

53

Uganda
0.5%

-1

0

1

2

3

4

5

Annualized increase in access to clean cooking (2014 - 2018, pp)
Low income

Lower middle income

Upper middle income

FIGURE 2.13 • The 20 countries with the fastest increasing percentage of population with access to clean
cooking fuels and technologies, 2014–18 average
Access deficit (millions)
0

200

400

800

0

25

50

727

India
Nigeria

173

Bangladesh

130

Indonesia

74

Myanmar

41

Viet Nam

37

Afghanistan

24

Annualized increase (pp)Access rate (%)

600

0.0

75

1.0

2.0

1.8

20

4.3

71
2.4

23
1.6

61

2.3

32
1.5

21
21

Côte d'Ivoire

18

26

1.7

Sri Lanka

15

28

1.8

13
8

Honduras

4

Congo

4

Mongolia

2

Georgia1

El Salvador

1

Eswatini

1

Guyana

0

5.0

1.6

Sudan

Peru

4.0

2.0

45
7

Ghana

Cambodia

3.0

24

2.1

46

1.4

19

1.8

76

1.6

53

2.1

28

1.8

46

1.7

77
88

1.5
1.8

50

1.6

73

Source: WHO.

URBAN-RURAL DIVIDE
A vast urban-rural disparity persists in access to clean cooking solutions. Urban areas enjoy greater access because
of infrastructure and availability of cleaner fuels and technologies. Figure 2.14 shows the percentage of the global
population with access to clean fuels and technologies in urban areas, in rural areas, and overall from 2000 to 2018. In
2018, the access rate was 83 percent (76–87) in urban areas and 37 percent (30–45) in rural areas.

100%

100

75%

75

50%

50

25%

25

0%

2000

2005

Urban

2010

Rural

2015

Overall0

Difference between urban and rural areas inaccess to clean cooking (percentage points)

Percentage of the population mainly using
each fuel type

FIGURE 2.14 • Percentage of people with clean cooking access in urban areas, rural areas, and overall (solidlines), and discrepancy in access between urban and rural areas (dashed line)

Difference

Source: WHO.

54

Tracking SDG 7: The Energy Progress Report 2020

0%

2000

2005

2010

2015

0

Difference
access to cl

Percentag

25

25%

Urban
Rural
Overall
Difference
Between 2000 and 2010 the disparity
between urban
areas and rural
areas in accessto clean cooking was fairly
constant at just over 50 percentage points (52pp [45–57] in 2010), but this has steadily fallen over the past decade,as illustrated in Figure 2.14, to 46pp (36–55) in 2018. This is explained by trend changes in the annual increase inaccess to clean fuels and technologies for urban and rural areas (Figure 2.15). In rural areas, the annual increase
has risen consistently, from only 0.2pp between 2000 and 2001 to 1.2pp between 2017 and 2018. In contrast, theannual increase in urban areas has fallen consistently over the past decade, from a high of 0.6pp between 2007 and2008 to only 0.2pp between 2017 and 2018. This means that while access has accelerated in the countryside, it has
been decelerating in urban areas. In fact, if observed trends continue and population growth outpaces access to clean
fuels, the proportion with access to clean cooking is projected to decline in urban areas as the new decade begins.
Meanwhile, some countries with rapid access growth will reach near-universal access, from which point increased
access is no longer possible.

FIGURE 2.15 • Annual increase in access to clean fuels and technologies for urban and rural areas

Annual increase in access to clean fuels and technologies(percentage points)

1.2

0.8

0.4

0

2000

2005

2010
Urban

2015

Rural

Source: WHO Global Household Energy Model (Stoner and others 2019).

A deeper analysis of individual fuel access, at country and region levels, can help gauge the effects of current policies
on household energy use and inform future policies and programs. Using estimates derived from household surveys
and advanced modeling techniques, a few notable trends can be seen across regions and countries.

CHAPTER 2 • Access to clean fuels and technologies for cooking

55

FIGURE 2.16 • Percentage of people using each cooking fuel type, for urban areas, rural areas and overall in
low- and middle-income countries
Urban

Rural

Overall

Percentage of the population mainly
using each fuel type

80%

60%

40%

20%

0%
2000

2005

2010

2015

Unprocessed Biomass

2000

2005

2010

Charcoal

2000

2015

Coal

Kerosene

2005

Gas

2010

2015

Electricity

Source: WHO Global Household Energy Model (Stoner and others 2019).

Among low- and middle-income countries, the use of gaseous fuels20 increased consistently from 30 percent (23–40)
in 1990 to 48 percent (42–56) in 2018, overtaking unprocessed biomass fuels21 as the dominant type of cooking fuelover the past decade (figures 2.16 and 2.17). Use of electricity for cooking has also risen, from 3 percent (2–4) in 2000
to 7 percent (4–12) in 2018, though the increase was far more notable in urban areas (Figure 2.16). Between 2000 and2010, increases in the use of clean fuels appear to be explained by steep declines in the use of coal, particularly in rural
areas where the use of coal dropped from 11 percent (6–17) in 2000 to 2 percent (1–6) in 2018, and also in the use ofkerosene, particularly in urban areas, where use dropped from 9 percent (7–10) in 2000 to 2 percent (1–3) in 2018. But
from around 2010 onwards, the use of unprocessed biomass fuels (wood, crop waste, and dung) has shown persistentdeclines, primarily in rural areas, where use of unprocessed biomass fuels dropped from 68 percent (63–72) in 2010
to 62 percent (54–69) in 2018.
Although the use of kerosene has dwindled worldwide (figures 2.16 and 2.17), it remains prominent in urban areas ofPercentage of the population using each fuel typelow- and middle-income countries in both Oceania(16middlepercent[8–35]
in 2018) and in Sub–Saharan Africa (9 percent
Low- andincomecountries[6–11] in 2018). Globally the proportion using charcoal is low (4 percent [3–4] in 2018), but in Sub-Saharan urban
areas its use has overtaken unprocessed biomass (29 percent [26–33] in 2018).
4%

3%

37%
2000

7%
37%

42%

44%
44%

2010

2018
49%
4%
2%
1%

3%

5% 9% 2%

3%
4%

Biomass

Charcoal

Coal

Kerosene

Gas

Electricity

20

Gaseous fuels, or simply “gas,” refer to liquefied petroleum gas, natural gas, or biogas.

21

Biomass fuels consist of raw/unprocessed biomass fuels (wood, crop waste, and dung), but not charcoal, which is presented separately.

56

Tracking SDG 7: The Energy Progress Report 2020

FIGURE 2.17 • Comparison of the percentage of people using each fuel type among low- and middle-income
countries in 2000, 2010, and 2018 Percentage of the population using each fuel type
Low- and middle- income countries

4%

3%

37%
2000

7%
37%

42%

44%

2010

44%

2018
49%
4%
2%
1%

3%
3%
4%

5% 9% 2%

Biomass

Charcoal

Coal

Kerosene

Gas

Electricity

Source: WHO Global Household Energy Model (Stoner and others 2019).

BOX 2.1 • SPECIFIC FUEL USE IN INDONESIA
Between 2000 and 2018, Indonesia saw the fastest growth in the percentage of people using clean fuels andtechnologies of any country, as illustrated in Figure B2.1.1. Here, the use of gaseous fuels—liquefied petroleumgas (LPG), natural gas, and clean biogas—rose considerably from 5 percent (1–13) in 2000 to 79 percent (65–88) in 2018.
In 2007, Indonesia launched an ambitious program to replace kerosene use with LPG in households and microbusinesses. The government had subsidized kerosene for decades, but the decline in domestic supply combinedwith rising oil prices (and the consequent increase in the subsidy) motivated an initiative to replace it. Indonesia
planned and executed its transition to LPG in several SDG 7 efforts, including feasibility studies, field tests,
distribution of conversion packages, strategic execution based on infrastructure readiness, and identificationof areas of high consumption potential and follow-up surveys to assess user satisfaction. Continuity of the
program is influenced by household income, infrastructure readiness, and access to sales points (Thoday andothers 2018).
Consequently, in urban areas, the rise in LPG use has come overwhelmingly at the expense of kerosene, the useof which has dropped from 70 percent (53–83) in 2000 to 2 percent (0–11) in 2018. The use of kerosene also
fell considerably in rural areas, from 22 percent (12–36) in 2000 to 1 percent (0–9) in 2018. However, the useof unprocessed biomass fuels also fell overall, dropping about 10pp between 2000 and 2010, after which thedecrease accelerated considerably, dropping a further 35pp between 2010 and 2018.

CHAPTER 2 • Access to clean fuels and technologies for cooking

57

FIGURE B2.1.1 • Estimates of the population (percentages) in Indonesia relying on individual fuels forcooking (2000–18), with associated 95 percent confidence intervals
INDONESIAINDONESIA
Urban
Urban

Percentage of the population mainly using
each
fuel type
Percentage of the
population
mainly using
each fuel type

100%
100%

Rural
Rural

100%
100%

75%
75%

75%
75%

75%
75%

50%
50%

50%
50%

50%
50%

25%
25%

25%
25%

25%
25%

0%
0%
2000
2005
2010
2000
2005
2010

2015
2015

Kerosene
Kerosene

0%
0%
2000
2005
2010
2000
2005
2010
Gas
Gas

Electricity
Electricity

Overall
Overall

100%
100%

2015
2015

Biomass
Biomass

0%
0%
2000
2005
2000
2005
Charcoal
Charcoal

2010
2010

2015
2015

Coal
Coal

Source: WHO Global Household Energy Model (Stoner and others 2019).

The effect of these efforts is illustrated in Figure B2.1.2. In 2000, 199 million (179–208) Indonesians did not haveaccess to clean fuels and technologies—78 million (64–86) in urban areas and 121 million (115–122) in rural
areas. In 2018, about a quarter as many people did not have access to clean cooking—54 million (31–88), 13
million (4–32) of whom live in cities, and 38 million (23–57) in rural areas—leading to greatly diminished healthoutcomes and increased economic and social burdens for Indonesia.
FIGURE B2.1.2 • Population without access to clean fuels and technologies in Indonesia: urban, rural,and overall
INDONESIAINDONESIA

Population without access to clean fuels andtechnologies
for cooking(millions)
Population
without accessto cleanfuels andtechnologies for cooking (millions)

200
200

150
150

100
100

50

50

0

02000
2000

2005
2005
Overall
Overall

2010
2010
Rural
Rural

2015
2015
Urban
Urban

Source: WHO Global Household Energy Model (Stoner and others 2019).

58

Tracking SDG 7: The Energy Progress Report 2020

POLICY INSIGHTS

L

ack of access to clean fuels and technologies for cooking contributes to 4 million deaths each year in low andmiddle-income countries. It has been linked to heart disease, stroke, chronic obstructive pulmonary disease,pneumonia, adverse pregnancy outcomes, and cancer. This pollution is not restricted, however, to the household
environment alone, as it contributes as well to localized pollution, disrupting regional environments. Household
air pollution affects climate change: cooking and heating account for some 25 percent of black carbon emissions
worldwide (Bond and others 2013), and around 30 percent of the wood fuel harvested globally is unsustainable, which
results in climate-damaging emissions equivalent to 2 percent of emissions worldwide (Bailis and others 2015).
These facts make a compelling case for policies on universal access to clean cooking fuels and technologies. These
policies should be informed by data and integrated into the national agenda, while taking regional variations into
consideration. More detailed national and regional data on cooking fuels will provide a more accurate picture of thesituation and furnish policy makers with more information (box 2.2).

BOX 2.2 • ENHANCED MONITORING: CORE QUESTIONS ON ELECTRICITYACCESS AND HOUSEHOLD ENERGY FOR HOUSEHOLD SURVEYS FINALIZEDNational household surveys are an essential tool in monitoring household energy use and producing better
understanding of the impacts on health and sustainable development. The data currently collected on householdenergy use offer us a snapshot of access. In the end, however, they provide insufficiently detailed information on
patterns of household energy use and the diverse effects of these patterns on health and the environment acrossthe globe. In recognition of these shortcomings, the World Health Organization and the World Bank’s Energy
Sector Management Assistance Program have developed a new set of household survey questions. These
questions were refined through a collaborative process involving a diverse set of policy makers, researchers,
and program implementation professionals through a series of expert consultations. These questions have also
been extensively piloted in the field.
Shortcomings in previous surveys
Historically, national surveys and censuses often included only a single question: Was the household connected
to a national electricity grid? This simplistic approach does not consider the quality and quantity of the service,
such as potential breakdowns, voltage fluctuations, and hours of supply. To fully capture the varieties ofhousehold access, the survey must include questions about off-grid options.
Similarly, national surveys and censuses have historically asked only about the use of the primary fuel used
for cooking. Other energy-intensive household activities (for example, heating and lighting or supplementarycooking) also produce emissions with adverse impacts. It is essential to collect data on all fuels and technologies
used for household cooking, heating, and lighting to fully capture the exposure to health-damaging household
air pollution. To account for fuel stacking and more accurately measure household exposure to air pollution,
surveys need to ask about all types of fuel and stoves used for household activities—both main and supplemental
fuels. Response options in the new core questions tie in directly to the WHO guidelines for indoor air quality:
household fuel combustion (WHO 2014), so survey results will be able to classify households according toevidence-based and consistent definition of clean or polluting fuels and technologies.
New core questions
The new core questions on electricity access and household energy for household surveys capture national
data on SDG 7, to “ensure access to affordable, reliable, sustainable, and modern energy for all,” specificallyindicator 7.1.1 on the proportion of the population with access to electricity, and indicator 7.1.2 on the proportionof the population with primary reliance on clean fuels and technologies.

CHAPTER 2 • Access to clean fuels and technologies for cooking

59

The core questions are available for download: https://www.who.int/airpollution/household/survey-harmoni
zation/en/. Supporting materials such as a guidebook for use by statistical offices are forthcoming.
Household exposure to air pollution and the household burden of fuel collection have been shown todisproportionately affect women and children. In order to assess the existence and magnitude of this trend ona global scale across diverse cultures and populations, the core questions capture data on the time burdens ofcollecting fuels and cooking, linked to identifying information on the age and sex of the primary cook and fuelcollector.
Stronger data can lead to stronger policies
Designing and implementing successful national and subnational strategies to promote cleaner and safer
household energy require a detailed understanding of current energy use. The questions presented in this guide
have a central goal: to fill the data gaps enumerated above and, by standardizing survey questions, to enablecross-national comparison and validation of data. Better data will assist in the design of policies that encourage
uptake and sustained use of clean household fuels and technologies.

GEOGRAPHIC VARIATIONS
The global transition from polluting to clean household energy use is proceeding too slowly. But more rapid progress ispossible with the right mix of national policies, programs, and targeted interventions. For example, since 2001 Indonesia
has prioritized the transition to clean cooking fuels, reducing the number of people using polluting fuels for cooking by
almost 75 percent. In 2016, India launched Pradhan Mantri Ujjwala Yojana scheme, which prioritizes LPG connections
to rural households to benefit women living below India’s poverty line. Nigeria launched a campaign in Lagos andAbuja to disseminate information about LPG and encourage the switch to this fuel for cooking. In Bangladesh thegovernment has worked to create awareness among users and promoted LPG as the cooking fuel for households; it
has also reinforced monitoring systems to ensure safety and security. These countries, together with Myanmar, Viet
Nam, and Afghanistan, were among the 20 countries with the largest populations lacking access to clean cooking
during the period 2014–18. But because of efforts to transition, they were also among the 20 countries with the fastestincreasing access to clean fuels for the same period.
Rural areas across the globe have seen vast improvements: more than a quarter of a billion people have gained accessto clean cooking fuels since 2010. Despite increasing rural access to clean cooking fuels, urbanization is outpacing
the expansion of access. Furthermore, slum populations are often not captured in surveys. People living in densely
populated settings, including humanitarian camps and slums, often rely on polluting fuels to meet their daily energy
needs. Access to clean cooking fuels and technologies, while more readily available in urban areas, are still hindered inslums. Policymakers need to focus on this shortfall in access.

YOUTH, GENDER, AND HEALTH IMPLICATIONS
During 2018, 2.8 billion people were exposed to household air pollution. This exposure has been previously linked
to high blood pressure and respiratory and cardiovascular disease (Ezzati and others 2007; McCracken and others2007). The use of polluting fuels increases the risk of burns, injuries, poisoning, chronic headaches, and many otherills. The most vulnerable group thus exposed are women and children, as they are traditionally the procurers and usersof polluting household fuels.
In access-deficit countries in Sub-Saharan Africa, a sizable percentage of children spend time gathering fuels. In
addition, based on WHO statistics, the procurement of fuels is predominantly done by girls over boys (Figure 2.18).
This imbalance creates a bias from an early age as girls spend more time procuring fuels instead of other activities, forexample, receiving education.

60

Tracking SDG 7: The Energy Progress Report 2020

FIGURE 2.18 • Percentages of girls and boys who gather wood and water22 among all children in a given
country, by WHO region, for the period 2010–17

Percentage of girls who gather wood and water

80%
Central African Republic
70%
Malawi

Democratic Republic of Congo

Sierra Leone

60%
Nepal

50%

40%

30%
Sudan

Mauritania
20%

10% Viet Nam

0%
0%

10%

20%

30%

40%

50%

60%

70%

80%

Percentage of boys who gather wood and water
Central Asia and Southern Asia
Northern America and Europe

Eastern Asia and South-eastern Asia
Sub-Saharan Africa

Latin America & the CaribbeanWestern Asia and Northern Africa

Source: WHO.
Note: The World Health Organization categorizes the world into six regions: African Region (AFRO), Eastern Mediterranean (EMRO), European (EURO),
The Americas (PAHO), South-East Asia (SEARO), and the Western Pacific (WPRO). A list of the countries in each region is available here: https://www.
who.int/about/who-we-are/regional-offices

The degradation of household air quality because of polluting cooking fuels affects all household members. Somestudies show, however, that the concentration of particles in the air increases drastically during meal preparation. This
has an outsized effect on women and children because they are traditionally tasked with cooking.
Hours per week

Universal access to clean cooking fuels and technologies would also help attain other SDGs. The benefits of access toclean fuels and technologies include: better health and well-being (SDG 3), education (SDG 4), fewer gender inequalities
26.8(SDG 5), affordable and clean energy (SDG 7), economic growth (SDG8), sustainable cities and communities (SDG
11),
3.2
and climate action
(SDG
13).
Time spenton cooking

0.6
0.3

3.4
Time spent on
acquiring andpreparingcooking fuel

1.0
0.4
0.5

Female (15 or older)

22

Female (under 15)

Male (15 or older)

Male (under 15)

Due to limitations in data collection methods, specific data on fuelwood collection cannot be disaggregated.

CHAPTER 2 • Access to clean fuels and technologies for cooking

61BOX 2.3 • CLEAN COOKING AND GENDER
Percentage of girls who gather wood and water

80%

70%

60%

50%

40%

In developing countries around the world, millions of women and girls live in energy poverty, risking their lives
Central African Republic
every day by working long, arduous hours to secure the energy
needed by their households to cook their family’s
meals. The time spent cooking over inefficient stoves and procuring fuel restricts women’s ability to partake in
MalawiRepublicof Congo
paid, as well as educational, political,Democraticand social
activities,
thereby perpetuating gender inequality, economic
Sierra Leone
poverty, and a persistent drudgery trap. In addition to cooking, women also endure incredible hardships for fuelacquisition—walking long distances searching for fuel and carrying heavy loads of firewood and water. Displaced
women have even worse burdens, in many cases having toNepal
walk for hours to find firewood, sometimes spending
the night outside of camps set up for displaced people, and thus increasing their vulnerability to physical andsexual attack, dehydration, and other injuries. As the primary cooks in most developing-country households,
women are more susceptible than men to household air pollution, as they are more likely to inhale toxic smokefrom inefficient cooking fires.

Analyses of access to cooking fuels and technologies based on gender of head of household in Cambodia
and Nepal show significant
variability between countries and between urban and rural areas in-country. For
Sudan
example, the Mauritania
World Bank Multi-tier Tracking Framework (MTF) reports find that in Nepal (ESMAP 2018a), 43.6
20% percent of households run by women use clean-fuel stoves, compared to 36.1 percent of households headedby men. In Cambodia, meanwhile, no significant difference by gender exists in stove type for urban households(ESMAPViet
Nam 2018b); in the countryside, improved cooking stoves are less common among households headed by
10%
women (33.6 percent) than among households headed by men (41.7 percent). A common denominator in thesecountries: women are in charge of cooking, regardless of fuel and technology.

30%

0%0%An in-depth
10%analysis using
20% data from
30% Uganda shows
40%
50%
60% and male-headed
70%
80%that althoughfemalehouseholds

show similar rates of access to clean
cooking(at thelevel,
well as in urban and rural areas), femalePercentage
of boyswhocountry
gather wood
andas
water
headed households tend to have better access to clean cooking than male-headed households as household
expenditurelevel
Among therichest40 South-easternpercent of Asia
households,
women
have
greater access toCentral Asia
andincreases.
Southern Asia
Eastern
Asia andLatin America& theCaribbean
Northern
America andEuropeSub-SaharanWestern Asia
and Northern
AfricaIn terms ofimproved
cookstoves(Bhojvaidand others2014) Africa
and clean-fuel stoves (WLPGA
2014)
than men.
household time spent on cooking, women and girls spend much more time than men and boys. In Uganda,
women (15 years and older) spend on average 3.8 hours per day cooking, and girls spend close to 30 minutes.
In contrast, men and boys are virtually not involved in cooking. Similarly, female household members will often
spend much more time acquiring and preparing fuel than men and boys. In Uganda, women spend 3.4 hours per
week in cooking fuel acquisition and preparation—over 7.5 times more time than men (Figure B2.3.1).
FIGURE B2.3.1 • Time spent acquiring fuel and preparing food, by gender
Hours per week

26.8
Time spenton cooking

3.2
0.6
0.3

3.4
Time spent on
acquiring andpreparingcooking fuel

1.0
0.4
0.5

Female (15 or older)

Female (under 15)

Male (15 or older)

Male (under 15)

Source: Multi-Tier Framework, World Bank (https://mtfenergyaccess.esmap.org/), accessed in March 2020.

62

Tracking SDG 7: The Energy Progress Report 2020

The introduction of clean cooking fuels can drastically reduce the time women spend on unpaid household meal
preparation; clean cooking also promotes more cost-efficient fuels and thus financial savings in the long term.
The time and income recovered from these household activities free up space and opportunities for women andgirls, helping to lift them out of energy poverty. Time spent collecting fuelwood can be intensive: in India, timespent collecting firewood ranges from three to ten hours per week (Jagoe and others 2014). Nigerian households
spend an average of 1.7 hours per day gathering firewood (WHO 2019). In Kenya, households working withimproved cookstoves saw the time spent collecting fuel drop from an average of 12 hours per week to 5 hours—
and most participants reported using the time saved for economically productive tasks (WLPGA 2014).
Case studies have shown that when women receive empowerment training to sell stoves, they can dramaticallyincrease sales. For example, in Nepal and Kenya women doubled sales after training. In a pilot project supportedby the Clean Cooking Alliance with the Girl Guides in Ghana, 200 girls received training in empowerment,
entrepreneurship, and cooking technologies and fuels. Afterwards, each household purchased efficient
cookstoves. As a result, the girls reported a 50 percent reduction in cooking time, as well as two hours saved
per firewood collection trip. In 2014, a research study commissioned by the Clean Cooking Alliance in Kenya
found that women cookstove entrepreneurs sold three times as many cookstoves as their male peers when
given the same training and support. Additionally, women’s networks provide access to consumers in hard-toreach markets, and women distributors better understand the needs of women and more easily approach theirclients.
When women are positioned as the critical stakeholders they are—both as users who will benefit from cleaner,more efficient stoves and fuels, and as entrepreneurs and employees in the value chain—their efforts clearly
spur widespread adoption. Women have a role to play in every segment of the cooking value chain, and theirinvolvement can scale adoption of cooking products and services, while boosting their livelihoods. Women’s
involvement in the clean cooking sector can spur widespread distribution and delivery of cooking fuels andtechnologies that will contribute to a thriving global industry.
Sources: Clean Cooking Alliance; Multi-Tier Framework, World Bank (https://mtfenergyaccess.esmap.org/).

LOOKING AHEAD
Universal access to clean fuels and technologies remains feasible if serious policy efforts are made to expand access.
Action is most urgently needed in Sub-Saharan Africa, given the stagnation of access levels in this region. All but one of
the countries with the greatest deficit (people without access) are in Sub-Saharan Africa. In order to achieve universal
access by 2030, efforts must include a focus in this area.
Cooking is multisectoral, and it demands multisectoral solutions. These include the Health and Energy Platform of
Action (HEPA), a multisectoral platform launched in 2019. Aiming to strengthen the political and technical cooperation
between the health and energy sectors at both global and country levels to accelerate the transition to clean energy,
HEPA’s initial focus is on clean cooking and electrification of health care facilities. To achieve universal access to clean
fuels and technologies, governments, civil society organizations, private sector, academia, and the financial sector all
must step up actions.
Major initiatives are needed to drive progress. Increased investment is key to encourage the uptake of clean cooking
solutions. Encouraging progress includes the recent formation of the Clean Cooking Fund under ESMAP, and action by
the Green Climate Fund and other bilateral programs promoting clean cooking. Governments need to set clear goals totransition away from polluting fuels such as unprocessed biomass and charcoal used in inefficient stoves.
In order to ensure that programs distributing new household energy technologies deliver the desired results, newprograms should ensure that fuels and technologies are clean for health as defined by the WHO guidelines for indoor
air quality: household fuel combustion. Some of the more-advanced biomass stoves do achieve the emission rate
targets spelled out in the guidelines; if national programs intend to distribute these stoves, the adoption of national
cookstove standards is valuable (WHO 2019). Standardization of cookstoves will support manufacturers, consumers,
and policy makers by improving clarity about the benefits of clean cooking solutions.

CHAPTER 2 • Access to clean fuels and technologies for cooking63

To demonstrate the viability of clean and sustainable cooking solutions, governments and donors should consider
providing supplemental funding for projects focused on electric stoves and biogas. Recent reports have highlighted
the versatility and feasibility of mini grids and solar panels (Couture and Jacobs 2019). The cost of cooking withelectricity, either via mini grids or solar panels has decreased significantly, putting this alternative well within the cost
range of other cooking alternatives. This cost reduction is viable due to a combination of two effects: first, the cost ofsolar modules and batteries has decreased by 30 to 50 percent since 2016. Second, more energy-efficient cooking
appliances, induction stoves, pressure cookers, and slow cookers decrease the electric power consumed per person.
For example, over a one-hour period a pressure cooker uses approximately one-quarter of the electricity needed tooperate an electric hot plate. In off-grid areas like slums, humanitarian camps, and rural areas, mini grids and solar
panels can also provide electricity for cooking and other household activities.
There is encouraging progress in the promotion of clean fuels, including LPG. Stoves that rely on LPG and pay-asyou-go financing schemes are scaling up in Tanzania, Kenya, and Rwanda, with pilots in Nairobi; Uganda, India, andGuatemala have plans to expand. Biogas systems offer an advantageous solution to smallholders with ample accessto agricultural and animal waste by integrating fertilizer supply, sanitation, and electricity, in addition to cooking fuel.
Policy models that integrate stoves and fuel sales are gaining attention from the private sector (Clean Cooking Alliance2019). In Rwanda and Zambia private initiatives combine biomass pellets with gasifier stoves to achieve high-quality
combustion. Viable alternative fuels such as agricultural waste from local farms or neighboring countries could help
reduce fuel costs.
Incentives to use clean fuels and efficient technologies must be both user-centered and suited to cooking practices in
the community while featuring technical performance, practicality, and safety (Shan and others 2017). Failures here
will likely defeat long-term adoption and exclusive use. Policies and programs tailored to surmount barriers are alsoneeded. They need to focus on local cooking practices, affordability, and end-user preferences. As ever, women are an
untapped resource for reaching the community. They also stand to benefit the most from transitions to clean cooking.
The WHO guidelines for indoor air quality: household fuel combustion (WHO 2014) include a good practicerecommendation calling for governments to consider investing in clean household energy interventions to achieve
climate change mitigation. Scaling up clean cooking is also a way for countries to achieve their nationally determined
contributions while delivering meaningful health benefits.

64

Tracking SDG 7: The Energy Progress Report 2020

METHODOLOGYDATA SOURCES
The WHO Household Energy Database keeps regularly updated nationally representative household survey data
(https://www.who.int/airpollution/data/household-energy-database/en/). It relies on a number of sources (see table2.1) and serves in this report as the basis for all modeling efforts (Bonjour and others 2014; Stoner and others 2019).
The database has 1,356 surveys taken in 170 countries (including high-income countries) between 1960 and 2018; 21
percent of the surveys cover the years 2013 to 2018 and 99 new surveys cover 2016 to 2018. Modeled estimates forlow- and middle-income countries are provided only if there are underlying survey data on cooking fuels, so there areno estimates for Bulgaria, Cuba, Lebanon, and Libya.
Population data are from United Nations Population Division.

MODEL
As household surveys are conducted irregularly and reported heterogeneously, the WHO (in collaboration with the
University of Exeter, UK) has developed the WHO Global Household Energy Model (GHEM) to estimate trends inhousehold use of six fuel types:


unprocessed biomass (e.g., wood)charcoal



coal



kerosene

gaseous fuels (e.g., LPG)electricity

Trends in fuel use by population proportions are identified through a Bayesian hierarchical modeling for each fuel type,both urban and rural, drawing on country survey data. Smooth functions of time were the only covariate. Estimatesfor overall “polluting” fuels (unprocessed biomass, charcoal, coal, and kerosene) and “clean” fuels (gaseous fuels,
electricity, as well as an aggregation of any other clean fuels like alcohol) are produced by aggregating estimatesof relevant fuel types. Estimates produced by the model automatically respect the constraint that the total fuel use
equals 100 percent.
The GHEM is implemented using the R programming language and the NIMBLE software package for Bayesian modelingwith Markov chain Monte Carlo (MCMC). Summaries can be taken to provide both point estimates (e.g., means) andmeasures of uncertainty (e.g., 95 percent credible and 95 percent prediction intervals). The GHEM is applied to the
WHO Household Energy Database to produce a comprehensive set of estimates, together with associated measuresof uncertainty, of the use of four specific polluting fuel groupings and two specific clean fuel groupings for cooking, bycountry, for each year from 1990 to 2018. Further details on the modeling methodology and validation can be found in
Stoner and others (2019).
Only survey data providing individual fuel breakdowns and with less than 15 percent of the population reporting“missing” and “no cooking” and “other fuels” were included in the analysis. Countries with no household fuel data butclassified by the World Bank as high income (37 countries) were assumed to have transitioned to clean householdenergy. They are therefore reported as having greater than 95 percent access to clean technologies and fuels; nofuel-specific estimates were reported for high-income countries. In addition, no estimates were reported for lowand middle-income countries without data (Bulgaria, Cuba, Lebanon, and Libya). Modeled specific-fuel categories
estimates were reported for 135 low- and middle-income countries and estimates of overall clean fuel use werereported for 190 countries.

CHAPTER 2 • Access to clean fuels and technologies for cooking

65UNCERTAINTY INTERVALS
Many of the point estimates we provide here are accompanied by 95 percent uncertainty intervals, which imply a 95
percent chance that the true value lies within the given range. Small annual changes in the point estimate may bestatistical noise arising from either the modeling process or survey variability, and may therefore not reflect a realvariation in the numbers relying on different fuels between years. The uncertainty intervals should therefore be taken
into account when assessing changes in the access rate, or in the use of specific fuels, between years.

GLOBAL AND REGIONAL AGGREGATIONSPopulation data from the United Nations Population Division were used to derive the population-weighted regionaland global aggregates. Low- and middle-income countries without data were excluded from all aggregate calculations;high-income countries were excluded from aggregate calculation for specific fuels.

ANNUALIZED GROWTH RATES AND FUTURE PROJECTIONS
The annualized increase in the access rate is calculated as the difference between the access rate in year 2 and that inyear 1, divided by the number of years to annualize the value:(Access Rate Year 2 – Access Rate Year 1) / (Year 2 – Year 1)
This approach takes population growth into account by working with the final national access rate.
Projected access rates, access deficits, and fuel use can be estimated using the GHEM, where uncertainty increases
the further into the future estimates are calculated, reflecting how country trends may shift based on how unsettled
they were during the data period.
Projections are hypothetical scenarios in which no new policies or interventions (positive or otherwise) take place, andas such are useful as baseline scenarios for comparing the effect of interventions.

TABLE 2.1 • Overview of data sources for clean fuels and technology
TYPE OF DATARESPONSIBLE
ENTITYNUMBEROF UNIQUE
COUNTRIESDISTRIBUTION OFDATA SOURCES(IN %)QUESTION

CensusNational statisticalagencies

108

18.40

What is the main sourceof cooking fuel in yourhousehold?

Demographic and Health
Survey (DHS)

Funded by USAID;
implemented by ICF
International

81

17.20

What type of fuel does yourhousehold mainly use forcooking?

Living Standard
Measurement Survey,
income expenditure survey,
or other national surveys

National statisticalagencies, supportedby the World Bank

26

3.00

Which is the main source ofenergy for cooking?

Multi-indicator cluster
surveyUNICEF80

10.90

What type of fuel does yourhousehold mainly use forcooking?

Survey on global AGEING(SAGE)

WHO

6

0.40

World Health Survey

WHO

50

3.80

National survey

106

35.80

Other

79

10.30

UNICEF = United Nations Children’s Fund; USAID = United States Agency for International Development; WHO = World Health Organization.

66

Tracking SDG 7: The Energy Progress Report 2020

REFERENCES
Bailis, R., R. Drigo, A. Ghilardi, and O. Masera. 2015. “The Carbon Footprint of Traditional Wood Fuels.” Nature Climate
Change 5 (January). https://doi.org/10.1038/nclimate2491.
Bhojvaid, V., M. Jeuland, A. Kar, J. Lewis, S. Pattanayak, N. Ramanathan, V. Ramanathan, and I. Rehman. 2014. “How Do
People in Rural India Perceive Improved Stoves and Clean Fuel? Evidence from Uttar Pradesh and Uttarakhand.”International Journal of Environmental Research and Public Health 11 (2): 1341–58. https://doi.org/10.3390/
ijerph110201341.
Bond, T. C., S. J. Doherty, D. W Fahey, and many others. 2013. “Bounding the Role of Black Carbon in the Climate System:
A Scientific Assessment.” Journal of Geophysical Research: Atmospheres 118 (11): 5380–5552. https://doi.
org/10.1002/jgrd.50171.
Bonjour, S., H. Adair-Rohani, J. Wolf, N. G. Bruce, S. Mehta, A. Prüss-Ustün, M. Lahiff, E. A. Rehfuess, V. Mishra, andK. R. Smith. 2013. “Solid Fuel Use for Household Cooking: Country and Regional Estimates for 1980–2010.”
Environmental Health Perspectives 121(7):784.
Clean Cooking Alliance. 2019. “Clean Cooking Industry Snapshot: An Inaugural Report on Sector Investment andInnovation.” https://www.cleancookingalliance.org/reports/2019-Clean-Cooking-Industry-Snapshot/2019Clean-Cooking-Industry-Snapshot.html#page=1.
Couture, T. D., and D. Jacobs. 2019. “Beyond Fire: How to Achieve Electric Cooking.” World Future Council, The Hague.
May. https://www.cleancookingalliance.org/reports/2019-Clean-Cooking-Industry-Snapshot/2019-CleanCooking-Industry-Snapshot.html#page=1.
ESMAP (Energy Sector Management Assistance Program). 2018a. “Nepal—Beyond Connections: Energy Access
Diagnostic Report Based on the Multi-Tier Framework.” Washington, DC: World Bank https://energydata.info/
dataset/nepal-multi-tier-framework-mtf-survey/resource/35124cc5-0ebf-49c7-b7df-ec7fc961eb1d.
ESMAP. 2018b. “Cambodia—Beyond Connections: Energy Access Diagnostic Report Based on the Multi-Tier
Framework.” Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/29512.
Ezzati, M., H. Saleh, and D. M. Kammen. 2000. “The Contributions of Emissions and Spatial Microenvironments to
Exposure to Indoor Air Pollution from Biomass Combustion in Kenya.” Environmental Health Perspectives 108:
833- 839. doi: 10.1289/ehp.00108833.
IEA (International Energy Agency). 2019. World Energy Outlook 2019. Paris: International Energy Agency, https://www.
iea.org/reports/world-energy-outlook-2019.
Jagoe, K., M. Rossanese, D. Charron, and many others. 2020. “Sharing the Burden: Shifts in Family Time Use, Agency,
and Gender Dynamics after Introduction of New Cookstoves in Rural Kenya.” Energy Research and Social
Science 64 (June). https://doi.org/10.1016/j.erss.2019.101413.
McCracken, J. P., K. R. Smith, A. Díaz, M. A. Mittleman, and J. Schwartz. 2007. “Chimney Stove Intervention to ReduceLong-Term Wood Smoke Exposure Lowers Blood Pressure among Guatemalan Women.” Environmental Health
Perspectives 115: 996–1001.
Shan, Ming, Ellison Carter, Jill Baumgartner, Mengsi Deng, Sierra Clark, James J. Schauer, Majid Ezzati, Jiarong Li, Yu Fu,
and Xudong Yang. 2017. “A User-Centered, Iterative Engineering Approach for Advanced Biomass Cookstove
Design And Development.” Environmental Research Letters 12(9).
Stoner, Oliver R., Gavin Shaddick, Theo Economou, Sophie Gumy, Jessica Lewis, Itzel Lucio, Giulia Ruggeri, and Heather
Adair-Rohani. 2019. “Global Household Energy Model: A Multivariate Hierarchical Approach to Estimating
Trends in the Use of Polluting and Clean Fuels for Cooking.” arXiv e-prints. https://arxiv.org/abs/1901.02791.
SEforAll (Sustainable Energy for All). 2019. Energizing Finance: Understanding the Landscape, 2019. https://www.
seforall.org/sites/default/files/2019-11/EF-2019-UL-SEforALL-w.pdf.

CHAPTER 2 • Access to clean fuels and technologies for cooking

67Thoday, K., P. Benjamin, M. Gan, and E. Puzzolo. 2018. “The Mega Conversion Program from Kerosene to LPG in
Indonesia: Lessons Learned and Recommendations for Future Clean Cooking Energy Expansion.” Energy for
Sustainable Development 46: 71–78.
WHO (World Health Organization). 2014. WHO Guidelines for Indoor Air Quality: Household Fuel Combustion. Geneva:
WHO. https://www.who.int/airpollution/guidelines/household-fuel-combustion/en/.
WHO. 2019. “Building Country Capacity towards Clean Cooking Solutions: The Importance of Setting Standards.”
Expert consultation, Kampala, Uganda, July 22–26. https://www.who.int/airpollution/events/standards_
workshop_kampala/en/.
WLPGA (World LPG Association). 2014. World LPG Association: Annual Report 2014. Neuilly-sur-Seine, France: WLPGA.
https://www.wlpga.org/wp-content/uploads/2015/09/wlpga-ar2014.pdf.

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Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 3: RENEWABLE
ENERGYRENEWABLE
ENERGY

Photo: Shutterstock

CHAPTER 3

MAIN MESSAGESThe global trend: Sustainable Development Goal (SDG) 7.2 posits a substantial increase in the share of renewableenergy in total final energy consumption (TFEC). Meeting this target will require the penetration of renewableenergy to accelerate in all three end uses—electricity, heat, and transport. In 2017, the share of renewable energy in
TFEC increased to 17.3 percent, up from 17.2 percent in 2016.23 This rise reflects a more rapid growth in renewables(2.5 percent) compared with the overall growth of TFEC (+1.8 percent). Renewable energy consumption has grown
fastest in the power sector; growth of renewables consumption in the heat and transport sectors has been muchslower. Excluding the traditional uses of biomass (see box 3.1 for definitions), the share of renewables in TFEC rose to
10.5 percent in 2017, up from 10.3 percent in 2016.

The target for 2030: Although there is no quantitative target for SDG 7.2, countries have agreed that the shareof renewable energy would need to accelerate substantially to ensure access to affordable, reliable, sustainable,
and modern energy for all. Despite impressive growth in renewable energy over the past decade, the world is not
on track to meet the SDG 7.2 target.



Regional highlights: At 69 percent of TFEC, Sub-Saharan Africa continues to show, by far, the highest shareof renewable energy. The traditional uses of biomass, however, still account for almost 85 percent of renewableenergy consumption in the region, while modern renewable energy is below the world average. Latin America
and the Caribbean, on the other hand, had the largest share of modern renewables (29 percent) thanks to theextensive use of modern bioenergy and hydropower. In Asia, modern renewable energy shares remained below
the global average at around 8 percent of the regional TFEC.



The top 20 energy-consuming countries: The share of renewable consumption varies by country. Between
2010 to 2017, 13 out of the top 20 energy-consuming countries increased their share of renewables. The United
Kingdom in particular saw the largest relative increase, led by wind energy. Yet in Brazil, India, Indonesia, Nigeria,
Pakistan, and Turkey, renewables have grown more slowly than total energy consumption.

Electricity: Renewable electricity consumption increased by almost 6 percent year-on-year in 2017. In relative
terms, this meant that the share of renewables in global electricity consumption reached 24.7 percent, the highestof all end-use sectors. With this growth, the renewables share in electricity surpassed its share in heat for the
first time in history. In terms of growth rate, however, this represents a deceleration compared with the record
year-on-year growth recorded in 2016. Lower hydropower output was the main reason behind the slower increase
in renewables.



Heat: Renewables used for heating increased by 1.1 percent, reaching 23.5 percent of total final heat consumption
in 2017, including traditional uses of biomass. The growth was led by modern renewable energy uses, whichgrew by 2.3 percent year-on-year in 2017. Overall, the share of modern renewables reached 9.2 percent of heatconsumed globally, up from 9.1 percent in 2016. Consumption of biomass for its traditional uses remained almost
unchanged (+0.3 percent year-on-year) in 2017 compared with 2016, still accounting for more than 14 percent of
global heat consumption.

Transport: The share of renewable energy in transport flattened in 2017, remaining at 3.3 percent in 2017. Mostof the renewable energy consumed came in the form of liquid biofuels, mainly crop-based ethanol and biodiesel,
thanks to policy support (among other factors) in Brazil, the European Union, and the United States. In 2017,consumption of electricity in the transport sector was 1.3 exajoules (EJ), of which 24 percent was renewable(0.3 EJ), representing 0.3 percent of global energy consumption in the transport sector.

23
Revised historical data have altered the historical time series of renewable shares in this report; they now present lower values than the timeseries shown in previous editions. More details on this shift can be found in the section of this chapter entitled “Are We on Track?”

71

0.3%

12%

2.5

0.2%

10%

2.0

ARE WE ON TRACK?

8%

0.0%

6%

1.5

EJ

0.1%

I

1.0

2011 20122013consumption,2014 2015 20162017
n 2017,2010
renewableenergyincludingthat of biomass
for its traditional uses, increased by 2.5 percent
0.5
year-on-year, a more rapid growth compared with global TFEC (+1.8 percent). As a result, the renewable energy share-0.1%
in TFEC increased from 17.2 percent in 2016 to 4%
17.3 percent in 2017—still lower than the all-time record share of
0.0
17.5 percent, achieved in 1999 (Figure 3.1).24
2010 2011 2012 2013 2014 2015 2016 2017-0.2%year, SDG 7 reported that the 2016 share of renewables
2%
Last
had
-0.5reached 17.5 percent. New data submissions in 2018–
19 indicate an important historical revision over published data from the previous year. Several African countries, aswell as developing countries in Asia, revised downward historical data on solid biomass and charcoal consumption-1.0-0.3%2000 to 2016. As a result, the share of renewables
0% declined
fromglobally by 0.1–0.3 percentage points throughout thehistorical timeseries.
On
the
one
hand,
this
downward
revisionslightly
increases
thedistance to target—i.e.,
the gap
Modern bioenergy
Traditionalusesof biomass% change in share of renewables (left axis)
between the current status and the objective of achieving substantial Hydropowerincreases in the share of renewables
by 2030.
Wind
Share of modern renewables (right axis)
The revision implies, however, that the consumption of biomass for traditional
uses in developingOther(non-OECD)
Asia
Solar PV
renewables
Shareof traditional
uses of biomass(right axis)
and Africa waslower
than previously
estimated,suggesting that these regions are making better use of resources. The
trend of rising shares of modern renewables was largely unaffected by the historical data revision.

Trends between 2000 and 2007 showed global declines in the share of renewables owing to faster growth from
non-renewable sources to meet surging global demand, in particular coal consumption in some emerging economies.
Since 2011, renewables have increased more rapidly than global energy consumption, leading to a steady increase in
their share of TFEC. Overall, bioenergy, including traditional uses of biomass, remains the largest source, accounting
for almost 70 percent of global renewable energy consumption, followed by hydropower, wind, and solar.
FIGURE 3.1 • Renewable energy consumption by technology, and share in total energy consumption,
1990–2017
20%

70

60
15%

50

40
EJ

10%
30

20

5%

10

0

1990

1993

1996

1999

Traditional uses of biomass
Solar PV

2002

2005

Modern bioenergy

Other renewables

2008

2011

Hydropower

2014

2017

0%

Wind

Share of renewables in TFEC (right axis)

Source: IEA and UNSD.

24
The data for figures 3.1–3.13 were obtained from the databases of the International Energy Agency and the United Nations Statistics Division.
Those databases are accessible at https://www.iea.org/data-and-statistics and https://unstats.un.org/unsd/energystats/.

72

Tracking SDG 7: The Energy Progress Report 2020

The share of renewable energy in TFEC continued to increase in 2017, albeit at a slower pace. This slowed growth is
explained, first, by the surge in global energy consumption (1.8 percent in 2017, compared with 1.1 percent in 2016).
Second, overall hydropower generation was lower, especially in Europe and China, more than offsetting the year-onyear increases seen in the Americas. Meanwhile, the absolute increase in generation from wind and solar doubled yearon-year, leading to an increase in the share of modern renewables (i.e., excluding traditional bioenergy), which reached10.5 percent in 2017, up from 10.3 percent in 2016.
After declines in 2015 and 2016, traditional uses of biomass increased in 2017 in absolute terms because overall
decreases in Asia could not offset additional consumption in Africa. Nevertheless, the share of such uses in TFEC
continued to decline, falling below 7 percent for the first time. This trend needs to accelerate to ensure access toelectricity through modern technologies. Despite progress, modern renewables must expand much more quickly tocompensate for falling shares of traditional uses of biomass and to achieve the SDG 7.2 goal of substantially increasing
the share of renewables by 2030 (Figure 3.2).

BOX 3.1 • “TRADITIONAL USES OF BIOMASS", DEFINED
The term “traditional uses of biomass” refers to the use of local solid biofuels (wood, charcoal, agriculturalresidues, and animal dung) burned with basic techniques, such as traditional open cookstoves and fireplaces.
Owing to their informal and noncommercial nature, it is difficult to estimate the energy consumed in suchpractices, which remain widespread in households in the developing world. For purposes of this report,“traditional uses of biomass” refers to the residential consumption of primary solid biofuels and charcoal in
non-OECD countries. Although biomass is used with low efficiency in OECD countries, as well—for example,
in fireplaces burning split logs—such use is not covered by the traditional uses of biomass cited in this report.
Traditional uses of biomass tend to have very low conversion efficiency (5–15%) and, as local demand may
also exceed sustainable supply, can often result in negative environmental impacts, notably deforestation. In
addition, emissions of high particulate matter and other air pollutants are produced. When combined with poor
ventilation, such pollutants create household indoor air pollution, which is responsible for a range of severe
health conditions and a leading cause of premature death. Even though biomass as it is traditionally used is, inprinciple, renewable, policy attention should focus on reducing it and encouraging the adoption of more modern
renewable heating and cooking technologies.
“Modern bioenergy” can be used efficiently for electricity generation, for industrial applications, for cooking in
efficient wood or pellet stoves and boilers, and for the production of biofuels for transport. Modern bioenergy—
along with solar PV, solar thermal, geothermal, wind, and hydropower—is one of the “modern renewables”
analyzed in this report.

CHAPTER 3 • Renewable Energy

73

FIGURE 3.2 • Share of renewable energy, modern renewable energy, and traditional uses of biomass, 2010–17 (left) and Renewable energy consumption growth by technology (right)
0.3%

12%

2.5

0.2%

10%

2.0

0.1%

8%

0.0%

6%

EJ

1.5

2010 2011 2012 2013 2014 2015 2016 2017
-0.1%

1.0

0.5
4%
0.0
2010

-0.2%

2%

-0.5

-0.3%

0%

-1.0

2011

2012

2013

2014

2015

2016

2017

% change in share of renewables (left axis)

Traditional uses of biomass

Modern bioenergy

Share of modern renewables (right axis)

Hydropower

Wind

Solar PV

Other renewables

Share of traditional uses of biomass (right axis)

Source: IEA and UNSD.

20%

70

60
15%

50

40
EJ

10%
30

20

5%

10

0

1990

1993

1996

1999

2002

2005

2008

2011

2014

2017

0%

Share of renewables in TFEC (right axis)

74

Tracking SDG 7: The Energy Progress Report 2020

LOOKING BEYOND THE MAIN INDICATORS

R

enewable energy has three main end uses: electricity, transport, and heat.25 The SDG 7.2 target calls for a“substantial increase” in the share of renewable energy, requiring an accelerated penetration of renewable energy
in all three end uses. Electricity accounted for almost two-thirds of renewable energy consumption growth from2016 to 2017, followed by heat (30 percent) and transport (6 percent). With this growth, renewables’ share in electricity
reached almost 25 percent and surpassed the renewable share in heat for the first time. The share of renewables(including traditional uses of biomass) in heat has been stable at around 23 percent since 2010 (Figure 3.3). The
stability in shares stems from two concurrent drivers: first, slow declines in traditional uses of biomass for cooking andheating, and, second, greater use of modern renewable technologies. The year-on-year increase in the direct use ofmodern renewables for heat reached 2.3 percent in 2017. For the first time since 2001 the share of renewable energy intransport did not rise, remaining at 3.3 percent, which is the lowest share among end uses. Biofuels account for mostof renewable consumption in transport, but renewable electricity use is also emerging thanks to the uptake of rail andelectric vehicles.
FIGURE 3.3 • Renewable energy share by end use, 1990–2017
30%

25%

20%

15%

10%

5%

Electricity

Heat including traditional uses of biomass

Heat excluding traditional uses of biomass

Transport

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

0%

Source: IEA and UNSD.

The global figure on the share of renewables conceals regional disparities in the penetration of renewable energy
and the role of traditional uses of biomass in country energy mixes (Figure 3.4). In 2017, Sub-Saharan Africa had by
far the highest share of renewable energy in TFEC. But traditional uses of biomass account for almost 85 percent of
Sub-Saharan Africa

25“End use” refers to the service for which energy is consumed. The services are classified into three categories: electricity end uses, transport end
Americaanduses, Latin
and heating.
For
the sake of simplicity, the latter is referred to in this report as “heat.” A fraction of electricity end uses overlaps with heat, as some
Caribbeanto produce heat. In this report, however, renewable electricity consumed to produce heat is accounted for under the electricity
electricitythe
is consumed
end use. Heat refers to the amount of non electric energy consumed for heating in industry and other sectors. It is not equivalent to the final energy
end use.
Central Asia andSouthern Asia

Eastern Asia and
CHAPTER3 • Renewable
South-eastern
Asia Energy
Oceania

75

5%

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

0%

total renewable energy consumption in the region. Latin America and the Caribbean had the largest share of modern
renewables among all regions thanks to the extensive use of modern bioenergy in transport and industry, in addition tohydropower electricity generation.
In Southern Asia as well as in Eastern
Asia andSouth-eastern
Asia, the penetration
Electricity
Heat including
traditional
uses of biomassof modern renewables inHeat
TFEC
remains
belowuses
the ofglobalaverage atTransport
around 8 percent. Outside of Latin America, Middle
excluding
traditional
biomass
Africa, Europe, Oceania, and Northern America had the highest share of modern renewables in final consumption in2017, led by bioenergy and hydropower, with wind and solar PV making growing contributions.
FIGURE 3.4 • Renewable share in total final energy consumption by region, 2017

Sub-Saharan Africa

Latin America andthe Caribbean
Central Asia andSouthern Asia
Eastern Asia andSouth-eastern Asia
Oceania

EuropeNorthern America

Northern Africa

Western Asia

0%

10%

20%

30%

40%

50%

60%

70%

80%

Hydropower

Wind

Solar thermal

Tide

Modern bioenergy

Solar PV

Geothermal

Traditional uses of biomass

Source: IEA and UNSD.

At the national level, the share of renewable consumption varies widely depending on resource availability, policy
support, and the effect of energy efficiency on growth in demand for energy. Between 2010 and 2017, 13 of the 20 largest
energy consumers increased the share of renewables (including traditional uses of biomass) in their consumption
mix. The United Kingdom saw the largest relative increase, with its renewable share tripling between 2010 and 2017.
Germany, Italy, France, and Japan also achieved remarkable growth, mostly in the power sector. In India, renewables
penetration in TFEC has declined since 2010. Although wind, solar PV, and modern bioenergy grew, the upturn could
not offset the welcome decline in the traditional uses of biomass and overall increases in energy consumption. In
Indonesia, Pakistan, and Nigeria, modern renewables have grown far more slowly than non-renewable energy
consumption (Figure 3.5). In absolute terms, China remains by far the largest consumer of all renewables, excluding
bioenergy, while its share of renewables in TFEC—including traditional uses of biomass—was 13 percent in 2017. Amongthe 20 countries, Brazil was the absolute leader, with a 45 percent share of modern renewables, followed by Canada at
23 percent.

76

Tracking SDG 7: The Energy Progress Report 2020

FIGURE 3.5 • Renewable energy share in TFEC, top 20 countries with the largest energy consumption, 2010
and 2017
90%
80%
70%
60%
90%
50%
80%
40%
70%
30%
60%
20%
50%
10%

% of RE in TFEC in 201010%

% of modern renewables in 2017

Nigeria

BrazilPakistanIndonesia

India

Canada

Italy

Spain

Germany

FranceChina

TurkeyUK

USA

MexicoJapan

Russia

20%

Korea

30%

Iran

Saudi
Arabia40%
0%% of traditional uses of biomass in 2017

% of RE in TFEC in 2010

% of modern renewables in 2017

Nigeria

BrazilPakistanIndonesia

India

Canada

Italy

Spain

FranceChina

UK

Germany

ELECTRICITYUSA

MexicoJapan

Russia

Korea

Iran

Saudi
ArabiaRE = renewable energy, TFEC = total final energy consumption.

TurkeySource:0% IEA and UNSD.

% of traditional uses of biomass in 2017

In 2017, renewable electricity consumption grew by almost 6 percent. The share of renewables in global electricity
consumption grew by 0.7 percentage points to reach 24.7 percent (Figure 3.6). The pace of growth slowed in comparison
30%
with 202016 despite slower overall growth in electricity demand. Lower hydropower output was the main reason behindthe slowdown. From 2016 to 2017, hydropower generation declined in major hydropower-producing countries—Brazil,
18
China, France, Italy, Spain, Pakistan, and Turkey—owing to low water availability. Nevertheless, hydropower remained
25%
the largest
source of renewable electricity, accounting for two-thirds of all renewable power generation.
16EJ

14 3.6 • Global renewable electricity consumption by technology, 1990–2017
FIGURE

20%

20
12

30%

18
10

15%
25%

16
8

10%

EJ

14
6

20%

12
4

5%

10
2

15%

8
0

1990

6
Hydropower
4

1993

1996

Other renewables

1999

2002

2005
Modern bioenergy

Solar PV

2008

2011

Wind

2
0

1990

Hydropower

1993

1996

Other renewables

1999
Solar PV

2002

2005
Modern bioenergy

2008
Wind

2011

2017

0%
10%

Share or renewables inelectricity consumption(right-axis)

5%

2014

2014

2017

0%

Share or renewables inelectricity consumption(right-axis)

Source: IEA and UNSD.

CHAPTER 3 • Renewable Energy77

In 2017, global solar PV and wind energy in electricity generation increased by 35 percent and 18 percent, respectively.
Accordingly, wind and solar PV together were responsible for almost 85 percent of renewable electricity growth yearon-year.
In addition to policy support, resource availability explains regional differences in renewable electricity consumption.
Latin America and the Caribbean commands the highest share of renewables in electricity consumption thanks toample hydropower and bioenergy resources (Figure 3.7). In Europe, Northern America, and Oceania, hydropower
remains the largest source of renewable generation, followed by wind and solar PV, which together provided on average
7–10 percent of total electricity generation in 2017. While hydropower remains the largest source of renewable electricity
in Africa too, governments have been introducing policies to foster deployment of wind and solar technologies, whichhave benefitted from recent cost reductions.
FIGURE 3.7 • Share of renewables in electricity consumption by region, 2017

Latin America andthe Caribbean
EuropeSub-Saharan Africa

Oceania

Northern America

Eastern Asia andSouth-eastern Asia
Central Asia andSouthern Asia
Western Asia

Northern Africa
0%

10%

20%

30%

40%

Hydropower

Wind

Solar thermal

Modern bioenergy

Solar PV

Geothermal

50%

60%
Tide

Source: IEA and UNSD.

5.0

90%

EJ

Among the top 20 energy consumers, the share of renewables in electricity ranges from less than 1 percent to 80
percent
4.5 (Figure 3.8). In 2017, China consumed more renewable electricity than any other country globally in absolute80%
terms, thanks to the country’s hydropower generation. China was already the largest consumer of solar PV in 2016. As
4.070%
of 2017, the country also became the largest consumer of electricity from wind and bioenergy, surpassing the UnitedStates,which
remainedthesecond-largest
consumerofrenewable
electricity
intheworld.
Braziland
Canada
have
by
3.5
60%
far the highest share of renewables in electricity generation thanks to large hydropower capacities. In most European
3.0
countries,
wind and solar PV were the largest sources of renewable electricity, with their share ranging between 15–50
50%
percent.
Between
2016 and 2017, the United Kingdom’s renewable electricity consumption increased by almost 20
2.5
percent, mostly thanks to offshore wind. With this growth, the country overtook Turkey, France, and Spain in justone
40%
year 2.0
and became the tenth-largest renewable electricity consumer among the top 20 energy consuming countries.
30%

1.5

20%

1.0

Saudi Arabia

Nigeria

Iran

Korea

Indonesia

Pakistan

MexicoTurkeyFrance

Spain

UK

Italy

RussiaJapan

Germany

India

Canada0%
Brazil

0.0
USA

10%

China

78

0.5

Tracking SDG 7: The Energy Progress Report 2020

Northern Africa
0%

10%

20%

30%

40%

Hydropower

Wind

Solar thermal

Modern bioenergy

Solar PV

Geothermal

50%

60%
Tide

FIGURE 3.8 • Consumption of electricity generated from renewable sources, top 20 countries, 2017
5.0

90%

4.5

80%

4.0

70%

3.5

60%

3.0

50%

EJ

2.5
40%

2.0

30%

1.5

20%

1.0

Hydropower

Modern bioenergy

Wind

Solar PV

Other renewables

Saudi Arabia

Nigeria

Iran

Korea

Indonesia

Pakistan

MexicoTurkeyFrance

Spain

UK

Italy

RussiaJapan

Germany

India

Canada0%
Brazil

0.0
USA

10%

China

0.5

% of renewables (right axis)

Source: IEA and UNSD.
RES = renewable energy sources, RES-E = renewable electricity

HEAT
Heat accounted for half of global final energy consumption in 2017, making it the largest energy end use worldwide(followed by transport and electricity generation). With coal, gas, and oil meeting more than three-quarters of global
heat demand, the sector remains heavily dependent on fossil fuels. Traditional uses of biomass—which have low
efficiency and generally result in adverse health and environmental effects—increased slightly (+0.3 percent) in 2017;
such uses still account for more than 14 percent (25.2 EJ) of global heat consumption (Figure 3.9). Consumption ofmodern renewable energy for heat increased 2.3 percent in 2017, representing 9.2 percent of the heat consumed
globally (up from 9.141 percent in 2016). A gradual transition away from the traditional uses of biomass to clean
and modern cooking fuels, technologies, and services—mainly in developing countries, as indicated in the SDG 7.1
target—requires more policy attention. A faster deployment of modern renewables for heating, one that can replace
traditional uses of biomass and fossil fuels, remains key to achieving both the SDG 7.2 and SDG 7.1 targets by 2030.

CHAPTER 3 • Renewable Energy

79

FIGURE 3.9 • Renewable heat consumption by source and sector
45

20%

40

18%

35
30

16%

35

25

14%

30

12%

EJ

25

20
EJ

10%
20

15

8%
10

6%
4%

Traditional uses of biomass

5

Industry

Modern bioenergy% of traditional uses of biomass in heat

Geothermal

Buildings

2017

2007

1997

2017

2007

1997

1997

0

2017

2014

2011

2008

2005

2002

1999

0%
1996

0
1993

2%

1990

5

2017

10

2007

15

Other

Solar thermal

Unspecified% of direct use of modern renewables in heat (right axis)

Source: IEA and UNSD.
Note: Indirect consumption of renewable heat through renewable electricity is not represented in this figure.

1680%
The consumptionof modern bioenergy increased by 2 percent in 2017. Bioenergy makes up around 90 percent(14.2EJ) of direct modern uses of renewables for heat and represents more than three-quarters of renewable district heat
14 26 Industry is responsible for two-thirds of modern bioenergy use, most of which is concentrated in subsectors
70%
globally.
producing biomass residues on site, such as the wood, pulp, and paper industries, as well as the food and tobacco
1260%
industries.

EJ

50%
Global10solar thermal consumption increased 3.3 percent in 2017, amounting to 1.3 EJ. The large majority corresponds
to domestic solar water heaters, although large-scale systems for district heating and industrial applications continue
8 as a niche market. There is vast untapped potential for low-temperature industrial processes, but speeding40%
to develop
deployment will require overcoming relatively high up-front costs and lack of awareness. China leads the solar thermal
30%
market,6with 70 percent of global installed capacity in 2017, although capacity growth has slowed in recent years
owing
to reduced construction, market saturation, competition with other technologies, and the phaseout of incentives.
420%

Sub-SaharanAfricaEastern Asia
and Southeastern Asia

Central Asia
and Southern
Asia

North
America andEuropeLatin America
and theCaribbean

Western Asia
and Northern
AfricaTraditional uses of biomass

Geothermal

Solar thermal

Modern bioenergy

2017

1990

2017

1990

2017

1990

2017

1990

2017

1990

2017

1990

2017

1990

Meeting less than 0.5 percent of global heat demand, geothermal heat is the smallest renewable heat source. Bathing
210%
and spaceheating (via district heating) are the most prevalent applications globally. Development of geothermal
systems remains limited to a few countries, with China and Turkey alone accounting for 84 percent of geothermal heat
00%EJ toconsumption
worldwide. Direct use of geothermal heat increased 6.8 percent in 2017, contributing just over 0.6
the renewable heat supply.
Oceania% of traditional uses of biomass in heat (right axis)% of direct modern renewables in heat (right axis)
26
Renewables also contribute to heat supply indirectly through renewable electricity used for heating. Taking these indirect uses into account,renewable electricity, used chiefly in buildings, is the second-largest modern renewable heat source after bioenergy. It accounted for an estimated onethird of the increase in total (direct and indirect) modern renewable heat consumption in 2017, owing to the combination of increasing penetration ofrenewables in the power sector and electrification of heating through the use of electric heat pumps and boilers.

80

Tracking SDG 7: The Energy Progress Report 2020

Traditional uses of biomass

Modern bioenergy% of traditional uses of biomass in heat

Geothermal

Solar thermal

Unspecified% of direct use of modern renewables in heat (right axis)

20%

2

10%

0

0%

Sub-SaharanAfricaEastern Asia
and Southeastern Asia

Central Asia
and Southern
Asia

North
America andEuropeLatin America
and theCaribbean

Western Asia
and Northern
Africa

2017

4

1990

30%

2017

6

1990

40%

2017

8

1990

50%

2017

10

1990

60%

2017

12

1990

70%

2017

14

1990

80%

2017

16

1990

EJ

FIGURE 3.10 • Renewable heat consumption by region, 1990 and 2017

Oceania

Traditional uses of biomass

Geothermal

Solar thermal

Modern bioenergy% of direct modern renewables in heat (right axis)% of traditional uses of biomass in heat (right axis)

Source: IEA and UNSD.
Note: Indirect consumption of renewable energy through electricity for heat is not included in this figure.

The traditional uses of biomass are concentrated in Sub-Saharan Africa and Asia (Figure 3.10), with, in descendingorder, India, Nigeria, China, Indonesia, and Pakistan together accounting for more than 60 percent of global
consumption. Stable traditional consumption of biomass at global scale hides disparate trends across regions: inEastern Asia, consumption declined significantly over the past decade, especially in China, while in Sub-Saharan Africa
consumption surged, driven by population increases.
Brazil, China, India, and the United States together accounted for more than 40 percent of global modern renewable
heat consumption in 2017 (Figure 3.11). This results from the hefty consumption of bioenergy in the pulp and paperindustry and for residential heating in the United States; the extensive use of bagasse in the sugar and ethanolindustry in Brazil and India; and significant deployment of solar thermal water heaters in China. The European Union’s
Renewable Energy Directive, which promoted renewable heat consumption, was another factor, driving the expansionof residential wood and pellet stoves and boilers (e.g., in Italy, France, and Germany) and the use of biomass in district
heating (e.g., Nordic and Baltic countries, Germany, France, and Austria). In addition, the growing consumption ofrenewable electricity through electric heaters and heat pumps in China, the United States, and the EU contributed
indirectly to renewable heat consumption (IEA 2019b).

CHAPTER 3 • Renewable Energy

81

FIGURE 3.11 • Renewable heat consumption in top 20 countries, 2017
100%

7

90%

6

EJ

80%
5

70%

7
4

60%
100%
50%
90%

6
3

80%
40%

5
2

30%
70%
60%
20%
10%
50%

3
0

Iran

Korea

Russia

UK

Japan

Spain

TurkeyMexicoItaly

CanadaFranceGermany

Source: IEA and UNSD.

Pakistan% of modern renewables in heat (right axis)

USA

Modern bioenergy

Note: Indirect consumption of renewable energy through electricity for heat is not included in this figure.

Traditional uses of biomass

Geothermal% of traditional uses of biomass in heat (right axis)

Solar thermal

Modern bioenergy% of modern renewables in heat (right axis)

TRANSPORT

Saudi Arabia

30%
20%
10%
0%

Saudi Arabia

Iran

Korea

Russia

UK

Japan

Spain

TurkeyMexicoItaly

CanadaFrancePakistanUSA

BrazilSolar thermal

Brazil% of traditional uses of biomass in heat (right axis)

Indonesia

Geothermal

Nigeria

Traditional uses of biomass
China

India

0

Germany

1Indonesia

Nigeria

China

2

0%
40%
India

EJ

4
1

The share of renewable energy in transport remained stable at 3.3 percent in 2017 year-on-year (Figure 3.12), the lowest
EJ
of all end-use
sectors. The majority of the renewable energy consumed came in the form of liquid biofuels, mainly cropbased
ethanoland biodiesel blended with fossil transport fuels. Most of the remainder was from renewables-based
4.0
4.0%
electricity.
3.5

3.5%

FIGURE 3.12 • Renewable energy consumption in transport, 1990–2017
3.0

3.0%
EJ

2.5
4.0

2.5%
4.0%

2.0
3.5

2.0%
3.5%

1.5
3.0

1.5%
3.0%

1.0
2.5

1.0%
2.5%

0.5
2.0

0.5%
2.0%

0.0
1.5
1990

1993

1.0

1996

1999

Renewable electricity

2002

2005

2008

2011

Biofuels

Share of transport consumption (right-axis)

2014

2017

1.0%

0.5
0.0
1990

0.0%
1.5%

0.5%
0.0%
1993

1996

1999

Renewable electricity

2002

2005

2008

2011

Biofuels

Share of transport consumption (right-axis)

2014

2017

Source: IEA and UNSD.

82

Tracking SDG 7: The Energy Progress Report 2020

The share of renewable energy in transport is low (Figure 3.13). First, because biofuels are blended at low ratios withgasoline or diesel and, second, because the uptake of electric vehicles is still at an early stage. In addition, demand forfossil fuels for transport continues to grow. Petroleum-product consumption increased 15 percent from 2010 to 2017,with more than half of that growth occurring in the Asia-Pacific region. This has suppressed growth of the renewableenergy share in China and India, even as renewable fuel consumption has grown.
Lack of broad policy support is also at work in the low uptake of renewable energy in transport. Around 130 countries
consume no renewable energy in their transport sectors. Biofuel support policies exist in about 70 countries, anddemand for electro-mobility is growing in China, Europe, and the United States. But many countries have no policies
to support and stimulate low-carbon transport. As of 2017, only four countries had shares of renewable energy intransport that exceeded 10 percent: Brazil, Finland, Norway, and Sweden.
Furthermore, most of the transport-related renewable fuel consumption pertains to road vehicles, with minimal use
in aviation and maritime transport. This is due to lower availability of economic and technically viable renewable fuels,
compounded by even less policy support for their use in these long-haul sectors.
The United States and Brazil together accounted for 60 percent of renewable energy in transport in 2017. Shifting
market dynamics in other key countries have produced variable growth in renewable energy consumption over the
past ten years.

PJ

FIGURE 3.13 • Renewable fuel consumption in transport in selected countries
250

10%

200

8%

150

6%

100

4%

50

2%

0

2007

2012

2017

2007

Germany

2012
FranceBiofuels

2017

2007

2012
China

Renewable electricity

2017

2007

2012

2017

2007

India

2012

2017

0%

Indonesia

Renewable share (right-axis)

Source: IEA and UNSD.

In the transport sector, ethanol constitutes the largest share of renewable energy. But over 2013–17 the average annual
increase in renewable energy consumption from ethanol was less than half that achieved in the previous five-year
period. This is primarily because of the slowing expansion of ethanol consumption in the United States. Gasoline
blended with ethanol at 10 percent covers almost all demand, while higher ethanol blends (such as 15 percent) isrelatively minimal owing to limits in fuel-supply infrastructure and vehicle compatibility.
Europe has been a global leader in biodiesel consumption. But growth in demand has slowed. Consumption growthfrom 2013 to 2017 was a fifth of the levels reported for the preceding five years. A key factor was a decline in theGerman market, where consumption in 2017 was 20 percent lower than it was for 2008. In France and Spain, bycontrast, markets continue to grow.
In 2017, global consumption of electricity in transport was 1.3 EJ, of which 24 percent was renewable (0.3 EJ). Railconsumed most renewable electricity in transport, with a smaller but growing share from road electric vehicles, acategory that comprises cars, buses, and two- and three-wheel vehicles. The global electric car stock was around3 million vehicles in 2017 and surpassed 5 million in 2018. China has significantly higher demand for renewablesbased transport fuel. There, in 2017, over half of renewable energy in transport came from electricity, with the largest
consumption coming from two- and three-wheeler vehicles.

CHAPTER 3 • Renewable Energy83New fuels with the potential to increase the renewable share in transport are entering the market. Consumption ofhydrotreated vegetable oil, also known as renewable diesel, is on an upward trend, with demand growing in Europe
and the United States. Technically a “drop-in” fuel, HVO can be used unblended in some diesel engines and offers theprospect of increasing the renewable share without changing vehicle fleets or modifying fueling infrastructure.
Biomethane (or biogas upgraded to the quality of natural gas) also offers a means of increasing renewable energy intransport. A like-for-like replacement for natural gas in suitable vehicles, it holds particular potential for road freight,
where a strategic rollout of fueling infrastructure along key transport corridors could attract a relatively large share ofdemand, and for captive fleets, where vehicles operate on set routes and refuel at depots.
Progress is also evident in renewable aviation fuels. Flights using biofuel blends have surpassed 230,000; continuous
biofuel supply is available at six airports; and there is policy support for their use in the United States and Europe.
Nonetheless, aviation biofuels account for less than 0.1 percent of fuel demand. Renewable fuel consumption in marinetransport remains nascent.

84

Tracking SDG 7: The Energy Progress Report 2020

POLICY INSIGHTS: A FOCUS ON ELECTRICITY
AND AUCTIONS

W

hile modern renewable energy has seen robust growth in the past few years, deployment would need toaccelerate much faster, especially in the heat and transport sectors, to ensure access to affordable, reliable,
sustainable, and modern energy for all by 2030. Most scenarios for the energy transition point in the same
direction. At the core of an energy transition thorough enough to reach the target of SDG 7 is increased electrificationof all end uses, combined with a decarbonized power sector.
Various policies and measures adopted worldwide have supported renewable energy deployment in the power sector.
The focus here is on the increasingly prominent role of auctions.
Between 2014 and 2018, instruments for competitively-set tariffs (auctions) have gained popularity, especially for
utility-scale applications, owing chiefly to their ability to procure renewables-based electricity at the lowest price. By
2018, more than 106 countries had adopted auctions at some point in time (REN21 2019; IRENA 2019a), with at least
68 countries announcing auctions during the reporting period covered here (2010–18) (ESMAP 2018).
As illustrated in Figure 3.14, price results for solar and onshore wind auctions have decreased in the past decade. In
2017, solar energy was contracted at a global average price of almost USD 58/MWh, down from USD 250/MWh in
2010. Wind prices also fell during that period, albeit at a slower pace—from USD 75/MWh in 2010 to USD 43/MWh in
2017. Plunging technology costs have led policy makers to consider auctions as a way to track the price of renewableenergy in their country. This downward trend continued for solar PV, though at a slower pace, reaching USD 56/MWhin 2018, while onshore wind prices rose slightly, reaching USD 48/MWh.
FIGURE 3.14 • Global weighted average prices resulting from auctions and capacity awarded each year,
2010–18
35

300

30

250

15

(GW)

Price
(USD/MWh)20
150

Capacity awarded

25
200

100
10
50

5

0

0
2010

2011
Capacity solar

2012

2013
Capacity wind

2014

2015
Solar

2016

2017

2018

Wind

Source: IRENA (2019a), based on BNEF (2019a) and PSR (n.d.).

AfricaCHAPTER 3 • Renewable Energy

Central and Western Asia

85

10
50

5

0

0

In the period2010
between 2017
total
of 111 GW2016
was auctioned
Solar PV2011 and 2018,2012 an estimated2013
2014volume2015
2017 or announced.
2018
and onshore wind—the variable renewable energy sources—accounted, respectively, for 52 percent and more thanCapacity
Solarthe use of auctions
Windvaried across regions as
36 percent of the totalCapacity
volumesolar(IRENA 2019a).
Aswindshown in Figure 3.15,
a function of varying levels of development of the renewable sector, power market structures and macroeconomic
contexts.
FIGURE 3.15 • Volume auctioned between January 2017 and December 2018, by region and technology (GW)

AfricaCentral and Western Asia

Americas

EuropeSouth and East Asiaand the Pacific
0

5

10

15

20

25

30

CSP

Small Hydro

35

40

Volume Auctioned (GW)
Solar PV

Onshore Wind

Offshore wind

Biomass

Biogas

Source: IRENA (2019a), based on BNEF (2019a) and PSR (n.d.).

Most African countries that held auctions in 2017–18 were doing so for the first time. Their auctions were dominatedby solar PV, where dedicated programs, such as the IFC’s Scaling Solar Program, succeeded in attracting investments
in Ethiopia, Madagascar, Senegal, and Zambia. The choice of auctions in Africa is driven for the most part by theirpotential for price discovery, especially when there is uncertainty regarding how to set the right price administratively(e.g., for a feed-in tariff). The flexibility in their design is also crucial: auctions can be tailored to specific contexts anddesigned to achieve low prices, through, for example, allocation of risks across multiple stakeholders. In this context,
the right risk allocation and transparent processes are key to success in attracting private investment, both domestic
and foreign. Auctions can be tailored to other policy purposes, as well, such as socioeconomic benefits, including job
creation and development of a local industry.
Countries in Europe and Southern and Eastern Asia and the Pacific auctioned much higher volumes, predominantly
solar PV and wind (both offshore and onshore). Some of those countries that had been supporting renewables throughadministratively-set tariffs (e.g., Germany, Japan, and Malaysia) turned to auctions to reduce the cost of support.
In addition, members of the European Union have been required to follow the European Commission’s Guidelines
on State Aid for Environmental Protection and Energy for 2014–20, which established market-based mechanisms as
the main instrument of support for renewables. The guidelines favor competition between renewable technologies
but explicitly allow for technology-specific auctions. Many countries adopted technology-specific auctions (namely,in Europe, Southern Asia, Eastern Asia, and the Pacific) to support the introduction of specific technologies into themix (e.g., offshore wind in Germany, Japan, and the Netherlands) or to achieve technology-specific targets (e.g., solar
PV in India). Increasing generation from variable renewable energy sources poses system integration challenges that
can also be addressed through auction designs that make geographical allocations sensitive to resource availability
and network integration costs. Strategies include introducing hard limits on volumes that can be commissioned incongested zones, procurement of specific projects (e.g., solar PV and batteries combined), or implementing priceadjustments to incentivize the production of power when and where it is most needed.

86

Tracking SDG 7: The Energy Progress Report 2020

Moving toward a higher share of variable renewable energy will require a more comprehensive and integrated approach
to power market design. The existing power markets (both regulated and liberalized) were originally designed aroundthe technologies of the fossil fuel era, where large, centralized, and dispatchable generation provided electricity toa largely passive demand. Such system designs can limit the deployment of renewable power, increase electricity
costs, and reinforce social inequalities (IRENA 2020b). The experience of auctions can assist in the redesign of power
markets.
As the results of renewable energy auctions fall more and more in line with prices of conventional generation, they
are being reshaped from support mechanisms to market mechanisms. In developed markets, their current role iscentered more on overcoming market structure failures rather than on providing support (IRENA 2020a). In Latin
America, in particular, auctions are already a functioning part of the power markets, and renewable energy generators
are able to achieve cost-competitiveness with fossil fuels (Batlle et al. 2018; Roques et al. 2017). Policy makers are thus
able to consider the restructuring of power markets, as auctions offer a viable solution for the large-scale procurementof low-cost renewable energy (IRENA 2020a, 2020b).
The restructuring of power markets should also enable responsive demand, including end uses, which are currently
dominated by fossil fuel solutions. Sector coupling through heat pumps, electrified industrial loads, and electricvehicles, for example, could complement future power sector needs, providing the ability to shift demand during
periods of high production of variable renewable energy. At the same time, further electrification using renewableenergy would assist the decarbonization of all end-use sectors, and the direct use of renewables could complement
nonelectrifiable loads.
The large-scale adoption of these technologies, however, will require proper planning for the energy sector as a whole.
Electrified loads and renewable energy should be deployed in a coherent fashion that enables and exploits synergies
between resources. Investments should prioritize long-term solutions so as to avoid stranding assets and locking
consumers into technologies not suited for the renewable energy era.
As renewable energy technologies become mainstream, the policies driving their deployment are quickly evolving. This
rapid evolution reflects many factors, among them changing market conditions, technical and socioeconomic hurdles,
and the need to ensure a just transition. Through the increasing use of auctions, policy makers have sought to procure
renewable electricity cost-effectively while fulfilling other, often country-specific social and economic goals. In otherwords, the trade-offs between achieving the lowest price and meeting other objectives can and should be consideredwhen designing auctions. Design elements such as winner selection criteria, limits on project size, and qualification
requirements, among others, can be introduced to include small and new players, foster the development of local
industries, create local jobs, contribute to subnational development, and engage communities, even if at a marginallyhigher price for electric power. But it must be remembered that these design elements, effective as they are, are just apart of a broader policy framework devoted to more just and inclusive energy transition, one that promotes renewables
deployment as a catalyst of inclusive and sustainable development and it rests on three transformative sets of policies:
deployment, enabling, and integrating policies (IRENA, IEA, REN21, 2018).

CHAPTER 3 • Renewable Energy

87BOX 3.2 • RENEWABLE ENERGY TO ADVANCE PROGRESS TOWARD SDG 8
An increase of renewable energy in the global energy mix translates into a number of tangible benefits, including
progress toward SDG 8 on jobs and economic well-being. As renewable energy has developed into a jobs engineof growing significance, the linkages between SDG 7 and 8 are increasingly acknowledged.
IRENA’s analysis shows that the number of renewable energy jobs worldwide has expanded from 7.3 million in2012 to 11 million in 2018 (IRENA 2019b). Modeling suggests that the energy transition could expand renewableenergy employment to 30 million by 2030 and 42 million by 2050 (IRENA 2020c). Although most jobs grew outof a modern energy context, recent growth in decentralized renewable energy solutions appears to be creating
jobs, too. For instance, GOGLA and Vivid Economics estimated direct off-grid solar employment in Southern
Asia and parts of Sub-Saharan Africa at 372,000 full-time-equivalent jobs (GOGLA 2018).
But in moving toward SDG 7, SDG 8, and the global energy transition, the centrality of jobs is about more thannumbers. A decent job should provide an adequate wage or salary, SDG 8 states, irrespective of gender, in a safeand productive workplace. In the energy transition, well-trained workers who stay long enough in their jobs will
be able to hone their skills and build the experience essential to success.
As of today, progress on employment related to achieving SDG 7 is evident but uneven. Most renewable energy
jobs are concentrated in key markets—namely, Brazil, China, Europe, India, and the United States—the home
states of the leading manufacturers and installers. Still, more countries are beginning to realize benefits of theirown. They will be in a strong position to benefit further to the extent they can combine ambitious renewableenergy deployment policies with related measures to build industrial capacities, expand education and skillbuilding, and ensure that the social benefits of the energy transition are broadly shared.
Benefits are still uneven with regard to the status of women. Although recognized as change agents in the
promotion of renewable energy, women remain underemployed and underrepresented amongst entrepreneurs.
A global survey indicated that women constitute only 21 percent of the wind energy workforce (IRENA 2020d),compared with 32 percent in renewables overall and 22 percent in traditional energy industries like oil andgas (IRENA 2019c). Substantial efforts are still needed to allow women to marshal their skills, talents, andperspectives in support of the coming transformation (IRENA 2019c; GWNET 2020).
Achieving SDG 7 and SDG 8 rests on the creation of more renewableenergy jobs and on gaining a better understanding of the required
skills. Additional data gathering and policy analysis are needed, which
led IRENA and several international partners to launch a joint initiativeat the start of 2020: for more information on the Sustainable Energy
Jobs Platform, please visit: http://sejplatform.org/.

88

Tracking SDG 7: The Energy Progress Report 2020

METHODOLOGYDEFINITIONS
Renewable energy sources (RES)

Total renewable energy from: hydropower, wind, solar photovoltaic, solar thermal,
geothermal, tide/wave/ocean, renewable municipal waste, solid biofuels, liquidbiofuels, and biogases

Renewable energy consumption

Final consumption of direct renewables plus the amount of electricity and heatconsumption estimated from renewable energy sources

Direct renewables

Final consumption of bioenergy, solar thermal, and geothermal energy

Total final energy consumption(TFEC)The sum of the final energy consumption in the transport, industry, and other sectors(also equivalent to the total final consumption minus non-energy use)

Traditional uses of biomass

Final consumption of traditional uses of biomass. Biomass uses are considered
traditional when biomass is consumed in the residential sector in non–Organisation
for Economic Co-operation and Development (OECD) countries, excluding Eurasia. It
includes the following categories in International Energy Agency statistics: primarysolid biomass, charcoal and non-specified primary biomass, and waste.
Note: This is a convention, and traditional consumption/use of biomass is estimatedrather than measured directly.

Modern renewable energy
consumption

Total renewable energy consumption minus traditional consumption/use of biomass.

METHODOLOGY FOR MAIN INDICATOR
The indicator used in this report to track SDG 7.2 is the share of renewable energy in total final energy consumption.
Data from the International Energy Agency (IEA) and United Nations Statistics Division (UNSD) energy balances areused to calculate the indicator according to the formula:where the variables are derived from the energy balance flows (TFEC = total final energy consumption as defined inTable 1, ELE = gross electricity production, HEAT = gross heat production) and their subscripts correspond to theenergy balance products.
The denominator is the total final energy consumption of all energy products (as defined in Table 1) while the numerator,
the renewable energy consumption, is a series of calculations defined as: the direct consumption of renewable energy
sources plus the final consumption of gross electricity and heat that is estimated to have come from renewablesources. This estimation allocates the amount of electricity and heat consumption to renewable sources based on theshare of renewables in gross production in order to perform the calculation at the final energy level.

CHAPTER 3 • Renewable Energy

89

METHODOLOGY FOR ADDITIONAL METRICS BEYOND THE MAIN INDICATOR
The amount of renewable energy consumption can be divided into three end-uses to refer to the energy service forwhich the energy is consumed: electricity, heat, and transport. They are calculated from the energy balance and aredefined as follows:
Electricity refers to the amounts of electricity consumed in the industry and other sectors. Electricity used in thetransport sector is excluded from this aggregation. Electricity used for heat-raising purposes is included because
official data at the final energy service is unavailable.
Heat refers to the amount of energy consumed-for heat-raising purposes in the industry and other sectors. It is not
equivalent to the final energy end use service. It is also important to note that in this chapter in the context of an “enduse”, it does not refer to the same quantity as the energy product “Heat” in the energy balance as used in the formula
above.
Transport refers to the amounts of energy consumed in the transport sectors. Electricity used in the transport sector
is mostly comprised of the rail and road sectors (and in some cases, pipeline transport). The amount of renewableelectricity consumed in the transport sector is estimated based on the share of renewable electricity in grossproduction.

90

Tracking SDG 7: The Energy Progress Report 2020

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GOGLA (Global Off-Grid Lighting Association) and Vivid Economics. 2018. Employment Opportunities in an Evolving
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REN21. 2019. Renewables 2019: Global Status Report. Paris: REN21.
Roques, F., and D. Finon. 2017. “Adapting Electricity Markets to Decarbonisation and Security of Supply Objectives:
Toward a Hybrid Regime?” Energy Policy 105: 584–596.
United Nations Statistics Division (UNSD). 2019. Energy Balances, 2019. New York: UNSD.

CHAPTER 3 • Renewable Energy91CHAPTER 4: ENERGYEFFICIENCY

ENERGYEFFICIENCY

Photo: Shutterstock

CHAPTER 4

MAIN MESSAGESGlobal trend: After a period of relative stability, the rate of global primary energy intensity—defined as thepercentage decrease in the ratio of global total primary energy supply per unit of gross domestic product (GDP)—
has slowed in recent years. Global primary energy intensity was 5.01 megajoules (MJ) per U.S. dollar (2011 PPP[purchasing power parity]) in 2017, a 1.7 percent improvement from 2016. This was the lowest rate of improvement
since 2010.



2030 target: Energy intensity improvements are moving further away from the target set under the United
Nations’ Sustainable Development Goal (SDG) for 2030. Between 2010 and 2017 the average annual rate of
improvement27 in global primary energy intensity was 2.2 percent. Although better than the rate of 1.3 percent
between 1990 and 2010, it is well below the SDG 7.3 target of 2.6 percent—which would have doubled the historic
trend. Annual improvement until 2030 will now need to average over 3 percent to meet the target set in SDG 7.3.
Even a positive rebound, as indicated by a preliminary estimate of 2 percent for 2019, remains well below the
3 percent annual increases needed to reach SDG target 7.3—or even the 2.2 percent seen between 2010 and 2017.



Regional highlights: Asia is where more robust, continuous improvements are seen in energy intensity than inthan any other world region. Between 2010 and 2017, primary energy intensity in Eastern Asia and South-eastern
Asia improved by an annual average rate of 3.3 percent. Similarly, in Central Asia and Southern Asia and Oceania,
the average annual improvement rate of 2.5 percent between 2010 and 2017 was above the global average(2.2 percent) and an improvement on historic trends. Rates of improvement were just below the global averagein Northern America and Europe (2.1 percent), with the lowest rates of improvement in Sub-Saharan Africa(1.3 percent), Western Asia and Northern Africa (1 percent), and Latin America (0.9 percent). Data on absoluteenergy intensity reveal wide regional differences: the most energy-intensive region is Sub-Saharan Africa, andLatin America and the Caribbean the least. These variations likely mirror not energy efficiency so much as
economic structure, energy supply, and access.

Top 20 countries in energy intensity: Comparing the periods 2000–10 and 2010–17, the annual rate of
improvement in primary energy intensity increased in 14 of the 20 countries with the largest total primary energy
supply in the world. But, of these, only 8 performed better than the global average. China continues to improveprimary energy intensity at the fastest rate, at an annual average of 4.5 percent between 2010 and 2017. Other
emerging economies with average energy intensity rates that are at or above those aimed for in SDG target 7.3
include India, Indonesia, and Mexico. Japan and the United Kingdom continue to improve their energy intensity
at rates beyond SDG target 7.3, thanks to decades of concerted effort toward energy efficiency and a shift in theireconomies toward producing high-value, low-energy goods and services.



End-use trends: Although global energy intensity improved across all sectors during the period 2010–17, the rate
differs by sector. Using different intensity metrics, the rate of improvement declined compared with the period
1990–2010 in all sectors except transport, where fuel-efficiency standards drove improvements. The decline in
the rate of improvement from one period to the other is most noticeable in services, agriculture, and, to a lesser
extent, industry. All three of these sectors were strongly influenced by emerging economies, which experienced
rapid improvements in energy intensity during the period 1990–2010 as they mechanized production and shiftedto higher-value goods and services.

27

Calculated as a compound average annual growth rate.

93



94

Electricity supply trends: The mounting share of renewables in electricity supply also improves the supply
efficiency by eliminating the losses that accompany the conversion of primary (non-renewable) fuels into
electricity. This relationship between efficient renewable electricity and a decrease in primary energy intensity
highlights the synergies between SDG target 7.2 and SDG target 7.3. In addition, nearly 40 percent of the average
efficiency of fossil fuel electricity generation is due to relatively more efficient gas-fired generation and theconstruction of highly efficient coal-fired generation in China and India. Major producing countries are seeing
declines in electricity transmission and distribution losses, which indicate higher rates of electrification and amodernized supply infrastructure.

Tracking SDG 7: The Energy Progress Report 2020

0%

-2.1%

-1.3%

-1%

-1.7%

ARE WE ON TRACK?

-2.6%

-2.6%

-3.6%

-3.0%

-2%

SDG 7 commits the world to ensure universal access to affordable, reliable, sustainable, and modern energy. Energy
efficiency supports all of SDG 7’s targets, but it is especially relevant to SDG target 7.3: doubling the current global
rate of energy efficiency by 2030. Energy efficiency is most commonlymeasuredin terms of “energy intensity,” or the
Additional
progressto 2030:-0.36% of energy used per unit of wealthratioofprimaryenergysupplytotheannualGDP
created—in
essence,theamount-3%
created. By using this measure of energy intensity to understand efficiency, we can observe how energy use rises orfalls while also looking for the development factors (social and economic) that may affect those rates. Energy intensity
declines as energy efficiency improves.
Progress toward SDG target 7.3 is measured by tracking the year-on-year percentage change in energy intensity.
-4%
Initially, an1990-2010
annual improvement
rate of 2.6 2015
percent per year
was recommended
by theUnited Nations
to achieve
2011-1420162017
2017-30
2017-2030 IEA
the target,
butperiod
since global progress has been slower than necessary, the annual improvement
now required totarget rate rate Sustainable
Base
(SDG)
Development
achieve SDG target 7.3 is at least 3 percent. Figure 4.1 illustrates global energy intensity improvements
since 1990.28
Recent numbers show that global primary energy intensity improved by 1.7 percent in 2017 to 5.01 Scenario
MJ/U.S. dollar(2011 PPP).

Annual change (left axis)

MJ/USD (2011) PPP

2017

2016

2015

2013

2014

2012

2011

2010

2008

2009

2007

2006

2005

2004

2003

2002

2001

2000

4
1999

-3%
1998

5

1997

-2%

1995

6

1996

-1%

1994

7

1993

0%

1991

8

1992

1%

1990

Annual change (%)

FIGURE 4.1 • Global primary energy intensity and its annual change, 1990–2017

Global primary energy intensity (right axis)

Source: IEA, UNSD, and World Bank (see footnote 2).
MJ = megajoule; PPP = purchasing power parity.

28
Most of the energy data in this chapter, including that used for many of the figures, come from the International Energy Agency’s (IEA) World
Energy Balances database (https://www.iea.org/data-and-statistics/) and the United Nations Statistical Division’s (UNSD) Energy Balances database (https://unstats.un.org/unsd/energystats/). GDP data are sourced from the World Bank’s World Development Indicators database (http://datatopics.worldbank.org/world-development-indicators/).

CHAPTER 4 • Energy Efficiency

95

FIGURE 4.2 • Growth rate of primary energy intensity, by period and target rate, 1990-2030
0%

-2.1%

-1.3%

-1%

-1.7%
-2.6%

-2.6%

-3.0%
-2%

Additional progressto 2030: -0.36%-

-3%

-4%
1990-2010
Base period

2011-14

2015

2016

2017

2017-30
target rate
(SDG)

Source: IEA, UNSD, and World Bank (see footnote 2).

The 2017 rate of 1.7 percent was the lowest rate of improvement since 2010, continuing the slowing trend since 2015
(Figure 4.2). As a consequence of this slowing, the average rate of improvement needed to meet SDG target 7.3 has
now300increased to 3 percent per year between 2017 and 2030,
a difference of 0.4 percent from the 2.6 percent initially5%estimated when the SDGs were enacted.
4%

250

3%
Index (1990 = 100)

200
2%
150
1%
100

0%
2015-16
-1%

50

-2%

GDP

2016

2012

2014

2010

2008

2006

2002

2004

1998

2000

1996

1992

1994

1990

0

96

2016-17-3%

Total primary energy supply

Primary energy intensity

Tracking SDG 7: The Energy Progress Report 2020

0%

LOOKING BEYOND THE MAIN INDICATORS
-2.1%

-1.3%

-1%

-1.7%
-2.6%

-2.6%

-3.0%

COMPONENT TRENDS-2%

The impact of improvements in primary energy intensity (the global proxy for improvements in energy efficiency)
is revealed by trends in its underlying components (Figure 4.3, left). Between 1990 and 2017, global GDP more thandoubled while global total primary energy supply increased by just over 50 percent. Although growth in primary energy
supply slowed markedly in 2015 and 2016, it picked up again in 2017, growing
by nearly 2 percent.
Additional progress-3%

to 2030: -0.36%

The difference in growth rates for global GDP and total primary energy supply is reflected -by consistent improvements
in global primary energy intensity, which fell more than 30 percent between 1990 and 2017, signaling trends inthe decoupling of energy use and economic growth. In the period 2010–17, global primary energy intensity fell by
10 percent, or just slightly more than the percentage drop observed between 2000 and 2010.
-4%

The recent slowdown
in the improvement
rate for 2015
energy intensity—from
2.6 percent
to 1.7 percent in 2017
1990-20102011-1420162017 in 20162017-30
rate energy supply
Base period that while GDP growth trended modestly upward, the growth rate fortarget(Figure 4.3, right)—means
primary(SDG)
tripled.
FIGURE 4.3 • Trends in underlying components of global primary energy intensity, 1990–2017 (left); andgrowth rates of GDP, primary energy supply, and intensity, 2015–17 (right)
5%

300

4%

250

3%
Index (1990 = 100)

200
2%
150
1%
100

0%
2015-16

2016-17

-1%

50

-2%

GDP

2016

2014

2012

2010

2008

2006

2002

2004

1998

2000

1996

1994

1992

1990

0

-3%

Total primary energy supply

Primary energy intensity

Source: IEA, UNSD, and World Bank (see footnote 2).
GDP = gross domestic product.

CHAPTER 4 • Energy Efficiency

97

BOX 4.1 • ESTIMATES FOR 2018 AND 2019 INDICATE SLOWING RATES OF
PRIMARY ENERGY INTENSITY IMPROVEMENT
Estimates from the International Energy Agency’s Global Energy Review: Energy and carbon emissions status
report 2020 show that the rate of improvement in global primary energy intensity continued to slow in 2018
but may have improved slightly in 2019 (Figure B4.1.1). Global primary energy intensity is estimated to have
improved by just 1.3 percent in 2018 and 2 percent in 2019, well below the 3 percent annual improvement target
required to achieve SDG target 7.3.
FIGURE B4.1.1 • Growth rate of global primary energy intensity, 2011–19
0%

-1.8%

-1%

-2.1%

-1.7%

-2.1%

-2.3%

-1.3%
-2.0%

-3.0%

-2.6%

-2%

-3%
2011

2012

2013

2014

2015

2016

2017

2018

2019

Source: IEA 2020.

Although it is estimated that efficiency continued to improve in 2018 and 2019, its impact has been overwhelmedby factors leading to increased energy demand, such as changes in energy users’ purchasing decisions andstructural shifts back toward more-energy-intensive industries. These factors, linked to strong economic growthand low energy prices, have combined with a static energy efficiency policy landscape to shrink improvements
in primary energy intensity. Progress in implementing new energy efficiency policies or strengthening existing
policies has been slow, limiting the ability of energy efficiency gains to offset the impact of economic growth
on energy demand. Slowing rates of improvement mean that additional effort will be required, on top of that
already needed, to reach SDG target 7.3.
Note: Further information available from IEA (2020).

Compound annual growth rate (%)

6%

4%

2%

0%

-2%

-4%

98

World

Oceania

CentralAsia andSouthern Asia

Eastern Asia andSouth-eastern
Asia

Total primary energy supplyGDP

Latin America
Northern
Sub-Saharan Western Asiaand theAmerica
Africaand Northern
Caribbean
and Europe
Tracking
SDG 7: The Energy ProgressAfrica
Report 2020
Primary energy intensity

0%

REGIONAL TRENDS-1.3%
Overall, since 2010, primary energy intensity has improved across the world, but noteworthy
differences in trends-1.7%-1.8% (Figure 4.4). Emerging economies in Eastern and South-eastern
are observed across regions
Asia have seen a rapid
-1%
-2.1%
-2.1% the riseincrease in economic activity; however,in primary energy supply associated with such growthhas been
-2.0%
-2.3%
mitigated in part by substantial improvements in energy intensity, which have put downward pressure on the global-3.0%America and Europe experienced a slight decrease inaverage. Over the same period, mature economies in Northern-2.6%
their primary energy consumption, which reflects slower economic growth and a decoupling of the economy fromenergyusage. This last accomplishment was made possible by a continued shift toward less energy-intensive industrial-2%
activities (such as services) and the improvements in energy efficiency observed when mature policies are in place,particularly in buildings (Northern America) and industry (Europe). In these economies, energy intensity improved at a
rate just below global trends, leading to an absolute level of energy intensity just below the global average (Figure 4.5).

From 2010 to 2017, economic activity steadily increased across Northern Africa, Oceania, Sub-Saharan Africa, and-3%Western Asia,
accompaniedin primaryenergy consumption
wellglobal average.
in20112012 by growth
2013
2014
2015
2016above the20172018 Improvements
2019
energy intensity in these regions have been modest and unable to offset the effects of economic growth on demand. In
absolute terms, significant differences exist between these regions, reflecting differences in their stages of development
and economic output (Figure 4.5). For example, economic output in Sub-Saharan Africa is highly energy intensive, atnearly 7 MJ/U.S. dollar (2011 PPP), partly reflecting the low value of economic output in this region, compared to 4.3
MJ/U.S. dollar (2011 PPP) in Northern Africa and Western Asia (Figure 4.5).
Despite continuing to record the smallest average gains in energy intensity improvement over the period 2010–17(less than 1 percent), the Latin America and the Caribbean region experienced a year-on-year improvement in energy
intensity of 2.1 percent in 2017, the largest gain there since 2011. This region is also the least energy intensive in theworld, at just below 4 MJ/U.S. dollar (2011 PPP) (Figure 4.5).
FIGURE 4.4 • Growth rate of GDP, primary energy demand, and regional energy intensity, 2010–17

Compound annual growth rate (%)

6%

4%

2%

0%

-2%

-4%

World

Oceania

CentralAsia andSouthern Asia

Eastern Asia andSouth-eastern
Asia

Total primary energy supplyGDP

Latin America
and theCaribbean

Northern
Americaand Europe

Sub-SaharanAfricaWestern Asia
and Northern
AfricaPrimary energy intensity

Source: IEA, UNSD, and World Bank (see footnote 2).
GDP = gross domestic product.

CHAPTER 4 • Energy Efficiency

99

FIGURE 4.5 • Primary energy intensity, by region, 2010 and 2017

MJ/USD (2011) PPP

8

6

4

2

Oceania

Central Asia
andSouthern Asia

Eastern Asia
andSouth-eastern
Asia

Northern
Americaand Europe

Latin America
and theCaribbean

Sub-SaharanAfrica2010 Primary energy intensity

2010 global primary energy intensity

2017 Primary energy intensity

2017 global primary energy intensity

Western Asia
and Northern
AfricaSource: IEA, UNSD, and World Bank (see footnote 2).
MJ = megajoule; PPP = purchasing power parity.

MAJOR COUNTRY TRENDS

Compound annual growth rate (%)

Rates 8%of improvement for primary energy intensity in the 20 countries with the largest total primary energy supply
would be central to realizing SDG 7.3. Over the period 2010 to 2017, 14 of these countries increased their rate of
improvement, but only 8 performed better than the global average, with 6 (China, India, Indonesia, Japan, Mexico, and6%
the United Kingdom) exceeding the level required by SDG target 7.3 (Figure 4.6).
Of these
4%six countries, four—China, India, Indonesia, and Mexico—are emerging economies. These countries have seen
rapid structural changes in their economies, changes that have moved them toward higher-value activities that create
more GDP for every unit of energy consumed. In these countries—particularly China and India—concerted efforts
2%
to introduce
energy efficiency policies over the period have quickened the pace of energy intensity improvements,
beyond the pace set by structural economic changes alone.
0%

The economies of Japan and the United Kingdom have expanded as their energy use declined. Both display energy
intensity improvement rates above the global average, suggesting that economic growth is being decoupled fromenergy-2%
use. A similar trend is observed in France, Germany, and the United States. High-value, service-related activities
are less energy intensive, and the economies in these countries all have strong, decades-long records of policy action
on energy-4% efficiency.

Total primary energy supply

100

GDP

Primary energy intensity

SDG 7.3 target

South Africa

ThailandTurkeyItaly

Nigeria

United K
ingdomMexicoSaudi Arabia

Indonesia

FranceIran, Islamic
Rep

Korea, Rep.

CanadaBrazilGermanyJapan

RussiaIndia

UnitedStatesChina

By contrast, Brazil and Iran are two major energy-consumers with worsening primary energy intensity, partly because-6%
their stagnant
economic conditions inhibit greater investment in industrial efficiency. Notably, both countries havesizable energy-intensive industry sectors. In Iran, where fossil fuels are plentiful, energy efficiency has not been apriority; meanwhile, generous government subsidies of fuel prices have further entrenched inefficient energy use.

Global average

Tracking SDG 7: The Energy Progress Report 20202017 Primary energy intensity

2017 global primary energy intensity

FIGURE 4.6 • Growth rate of GDP, primary energy demand, and intensity in the 20 countries with the highest
total primary energy supply, 2010–17
8%Compound annual growth rate (%)

6%

4%

2%

0%

-2%

Total primary energy supply

GDP

Primary energy intensity

SDG 7.3 target

South Africa

ThailandTurkeyItaly

Nigeria

United K
ingdomMexicoSaudi Arabia

Indonesia

FranceIran, Islamic
Rep

Korea, Rep.

CanadaBrazilGermanyJapan

RussiaIndia

UnitedStates

-6%

China

-4%

Global average

Source: IEA, UNSD, and World Bank (see footnote 2).
Note: Countries along x-axis ordered by total primary energy supply.
GDP = gross domestic product; SDG = Sustainable Development Goal.

FIGURE 4.7 • Primary energy intensity in the 20 countries with the highest total primary energy supply,
2010 and 2017

MJ/ USD (2011) PPP

10

8

6

2010 primary energy intensity

2010 global primary energy intensity

2017 primary energy intensity

2017 global primary energy intensity

South Africa

ThailandTurkeyItaly

Nigeria

UnitedKingdom

MexicoSaudi Arabia

Indonesia

FranceIran, Islamic
Rep

Korea, Rep.

CanadaBrazilGermanyJapan

RussiaIndia

UnitedStates

2

China

4

Source: IEA, UNSD, and World Bank.
Note: Countries along x-axis ordered by total primary energy supply.
MJ = megajoule; PPP = purchasing power parity.

CHAPTER 4 • Energy Efficiency

101

In absolute terms, the energy intensity of 10 of the top 20 energy-consuming countries remain above the global average,
compared to 9 in 2010. For example, energy intensity in Thailand grew from being below the global average in 2010, toabove it in 2017 (Figure 4.7). Since 2010, however, average global energy intensity has fallen by nearly USD 1/MJ (2011
PPP). Certain countries have made progress by moving further below global average energy intensity, including India,
Japan, and the United Kingdom. Others (such as China, South Africa, and the United States), despite remaining moreenergy intensive than the global average, are improving and shifting toward the global average.
Countries that have made the least progress include those where energy-intensive fossil fuel extraction is a major
economic activity—namely, Canada, Iran, Nigeria, and Russia.

BOX 4.2 • THE IMPACT OF PRIMARY ENERGY INTENSITY IMPROVEMENTS ON
GDP GROWTH
Improvements in primary energy intensity can have a marked effect on economic growth because less energyintensive economies create more wealth for every unit of energy consumed. This additional wealth is termed
the “productivity bonus”—that is, the bonus wealth created by annual energy intensity improvements. The
productivity bonus can also be used to track the economic opportunities missed because rates of energy intensity
improvement are slowing. By comparing the energy productivity bonus of a given year with a theoretical bonus
attained through a given higher level of efficiency that year, we can assess the opportunity cost of continuing tooperate in a business-as-usual manner.
Figure B4.2.1 shows the annual global productivity bonus from 2011 to 2017 and compares those improvements
against the productivity bonus that could have been created had the world achieved, with respect to theenergy consumed between 2011 and 2017, the 2.6 percent improvement rate in annual energy efficiency set
in Sustainable Development Goal (SDG) 7. As the figure shows, the world has fallen short of this goal since it
was announced, missing out on an average of USD 2 trillion per year, totaling more than USD 14 trillion over theseven-year period.
These global figures are driven by the largest economies—India, China, the European Union, and the UnitedStates. These four economies account for more than 60 percent of global gross domestic product, so as theircontributions to global growth increase and decrease in scale, so, too, do their energy intensity rates affect the
global efficiency measures. For example, in 2017, the global productivity bonus dropped by about 33 percent,from approximately USD 3 trillion in 2016 to approximately USD 2 trillion in 2017. China’s 2016 productivity
bonus, which was larger than all other countries combined, dropped by 42 percent in 2017 after its energy
intensity improvement rate more than halved from 6.9 percent in 2016 to 3.4 percent in 2017. The year-onyear change in China’s intensity contributed significantly to the loss of global productivity bonus, comprising
77 percent of the total loss. With the European Union and India responsible for 8 percent and 11 percent of thetotal loss, respectively, and the United States contributing an 11 percent gain, only 15 percent of the total effect is
attributable all other countries (IEA 2018). This comparison underscores the heavy hand these four economies
have over global efficiency and its impact on potential benefits brought with improvements.
Because of its capacity to increase economic productivity, energy efficiency can support not only SDG 7 but also
the world in its progress toward SDG 8, which calls for greater economic growth and productivity.

102

Tracking SDG 7: The Energy Progress Report 2020

FIGURE B4.2.1 • Energy productivity bonus, 2011–17
7000

USD Billions (2011) PPP

6000
5000
4000
3000
2000
1000

Energy productivity bonus at 2.6% improvement rate

2017

2016

2015

2014

2013

2012

2011

0

Energy productivity bonus at actual improvement rate

Source: IEA 2019a.
PPP = purchasing power parity.

END-USE TRENDS
Overall, during the period 2010–17, energy intensity improved in all sectors. Using different energy intensity metrics,
it is possible to examine the impact across sectors: compared with the period 1990–2010, the rate of improvement
slowed across all sectors, with the exception of transport (Figure 4.8).
In the industry sector, which comprises the most-energy-intensive economic activities, the annual rate of energy
intensity reductions dropped by roughly a third: from 3.7 percent to 2.5 percent. In spite of this slowdown, industry
energy intensity improved at the highest rate of all the sectors over the seven-year period, reflecting continued gains
in productivity. This is largely driven by emerging Asian economies such as China and India through, for example,
more efficient manufacturing processes for steel, cement, and chemicals (IEA 2017). The share in global productionof cement production in China and India (where energy intensities are among the lowest in the world) rose from
42 percent to 65 percent between 2004 and 2017. Furthermore, the policy framework for industry energy efficiency
tends to be more developed than for other sectors across countries worldwide (IEA 2018).
Between 2010 and 2017, the passenger transport sector experienced the second-highest rate of energy intensity
improvement, after the industry sector, at 2.3 percent. This increase is higher than the growth rate of 1.4 percent seenin the period 1990–2010. Similarly, energy intensity for freight transport improved at a faster rate compared with theprevious period. Nevertheless, its gains remained the lowest across all sectors, at only 1.3 percent. The transport sector
is a primary source of global emissions. As people travel more frequently and over longer distances, and consume
more imported goods, the sector is growing rapidly. Although stronger fuel efficiency standards in major markets are
improving energy efficiency, these are offset by transport behavior and consumer preferences. For example, consumer
demand for new and larger private road vehicles—comparatively energy-intensive forms of transport—remains strong,particularly as living standards rise in emerging economies (IEA 2019a, 2019b).
The residential sector, which is responsible for roughly 27 percent of electricity consumption worldwide, has seena minor slowdown in the rate of energy intensity improvement, from 1.9 percent to 1.5 percent. Demand for new
construction continues to swell with population growth, and recent years have seen rising demand for cooling and

CHAPTER 4 • Energy Efficiency

103

larger living spaces. Mitigating some of these effects would require greater ambition in the enforcement of buildings’
energy codes, especially in emerging economies, where a large share of new dwellings is being built.
Between 2010 and 2017, the service sector’s rate of energy intensity improvement slowed more starkly than that ofany other sector, falling from 5 percent in the previous period (1990–2010) to just 1.9 percent. There are two likely
reasons for this. First, the productivity gains brought about by the widespread computerization of this sector in
emerging economies had reached a saturation point. Second, services had become increasingly focused on higherend products, which tend to be more energy intensive to produce.
Similarly, the improvement rate for agriculture’s energy intensity more than halved—from nearly 3 percent in 1990–
2010 to just 1.3 percent between 2010 and 2017. As with the services sector, this is explained by a natural slowdown in
the rate of improvement in emerging economies with the advent of modern farming techniques following a period of
rapid mechanization that brought large gains in output for each unit of energy consumed.
FIGURE 4.8 • Growth rate of energy intensity by sector, 1990–2010 and 2010–17

Industry

Passenger transport

Services

Residential

Agriculture

Freight transport
-5%

-4%

-3%

-2%

-1%

0%

Compound annual growth rate (%)
1990-20102010-2017

Source: IEA, UNSD, and World Bank (see footnote 2).

Note: The measures for energy intensity used here differ from those applied to global energy intensity. Here, energy
intensity for freight transport is defined as final energy use per tonne-kilometer; for passenger transport it is final
energy use per passenger-kilometer; for residential use it is final energy use per square meter of floor area; in the
10%as final energy use per unit of gross value added
45% industry, and agriculture sectors, energy intensity is definedservices,(in 2011 U.S. dollars at purchasing power parity).

0%
-2%
-4%

ther
ables

017

014

011

008

005

002

999

996

993

990

ydro

-6%

30%

Tracking SDG 7: The Energy Progress Report 2020

clear

104

2%

Gas

35%

4%

Oil

40%

6%

Coal

Compound annual growth rate (%)

Generation efficiency (%)

8%BOX 4.3 • THE EFFECT OF STRUCTURAL FACTORS ON ENERGY DEMAND
In any year, energy demand is affected by a combination of energy-using activities, structural effects, andtechnical energy efficiency. Analysis of some of the world’s major economies shows that in 2012 and 2013,
structural effects reduced final energy demand by the same or more than the energy savings achieved bytechnical energy efficiency improvements alone (Figure B4.3.1).
However, in recent years, structural impacts have added to energy demand, offsetting some of the energy
savings brought about by technical efficiency improvements. Final demand across major economies grewby over 4 percent between 2015 and 2018, a slight increase over previous years. This reflects the effect of
population and economic growth, as well as structural shifts in the nature of energy-using activities in various
economic sectors. For example, evidence suggests that, on average, consumers have increased their travelling
distances, have changed their modes of transport to more energy-intensive options, own more appliances, andlive in buildings with larger floor areas. It is estimated that such structural effects alone were responsible for analmost 1.5 percent increase in energy use between 2015 and 2018 in some of the world’s major economies. The
recent shift in energy-using behavior in these countries might be at least partially related to low crude oil prices
during the period 2014–17.
FIGURE B4.3.1 • Combined effects of technical efficiency improvements and structural effects on
demand, annually, 2012–18
2012

2013

2014

2015

2016

2017

2018

0

-1

-2

EJ

-3

-4

-5

-6

-7
Structural change

Technical efficiency

Source: IEA 2019a.
Note: The “major economies” referred to in the above analysis are IEA Member Countries—Australia, Austria, Belgium, Canada, Czech
Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, the Netherlands,
New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom, and the United States—
plus Argentina, Brazil, China, India, Indonesia, and the Russian Federation.
EJ = exajoule.

7

6

5

4

EJ

CHAPTER 4 • Energy Efficiency

3105

Industry

TRENDS IN ELECTRICITY SUPPLY EFFICIENCY

Passenger transport

In addition to improvements in end-use efficiency, the rate of global primary energy intensity improvement is also
Services of fossil fuelinfluenced by changes in the efficiency of electricity supply. These include improvements in the efficiency
generation and reductions in transmission and distribution losses. The efficiency of fossil fuel electricity generation
has steadily improved since 2000, after showing flat rates of improvement during the preceding decade, to reachnearly 40 percent in 2017 (Figure 4.9, left).
Residential
Another factor affecting supply efficiency for global electricity is the share of renewable energy sources in the mix.
Statistically, renewable energy technologies are treated as being 100 percent efficient because no losses accompany
Agriculture
the conversion of resources such as sunlight and wind into electricity. So, the more renewable energy there is in themix, the greater the efficiency of electricity supply.
In 2017, renewable energy comprised only 17.3 percent of global electricity consumption; nevertheless,it madea notable
Freighttransport
contribution to energy efficiency. Between 2010 and 2017, renewable electricity sources other than hydropower grewat-5%
an annual average-4%
rate of 10 percent,up from 3 percent
in the period 1990–2010(Figure 4.9,
right). Hydropower
-3%
-2%
-1%
0%
electricity also grew at a faster rate than during the preceding period. Conversely, growth rates for fossil fuel generation
were all lower in 2010–17 than in theCompound
1990–2010
period. The combined effect of these growth rates has been toannual growth rate (%)
improve the overall efficiency of electricity supply by reducing losses experienced when converting primary energy
into electricity. That increasing the shareof renewable electricity
1990-20102010-2017helps to reduce primary energy intensity shows thesynergistic relationship between SDG targets 7.2 and 7.3.
FIGURE 4.9 • Trends in global fossil fuel electricity generation efficiency (left) and growth in electricity
generation by fuel type (right), 1990–2017
10%

45%

2%
0%
-2%

Gas

All fossil fuel generation

Coal

1990-2010

Other
renewables

2017

2014

2011

2008

2005

2002

1999

1996

1993

1990

Oil

Hydro

-6%

30%

Nuclear

-4%

Gas

35%

4%

Oil

40%

6%

Coal

Compound annual growth rate (%)

Generation efficiency (%)

8%

2010-2017

Source: IEA, UNSD, and World Bank (see footnote 2).

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BOX 4.4 • RELATIONSHIP BETWEEN THE EFFECT OF DEMAND- AND SUPPLYSIDE FACTORS ON EMISSIONS
Carbon emissions associated with the energy sector are one of the biggest contributors to human-induced
climate change. The goal of reducing global emissions therefore depends largely on reducing primary energy
intensity. Given that the time frame for action is shrinking, it is important to determine where in the energy
system countries should target their efforts.
Each year, changes in energy sector emissions are determined by a combination of factors, including changes
in energy-using activities, the intensity of both the supply and demand sides, and the emissions intensity of theenergy mix. Decomposition analysis allows for the identification of the factors responsible for annual changes
in emissions.
Analysis shows that in 2010, the rise in global emissions was driven by economic growth, a more emissionsintensive energy mix, and declines in the energy intensity of supply and demand. Since then, the major factor
helping to reduce the growth of energy-related emissions has been improved final energy intensity, thankslargely to efficiency gains in buildings, industry, and transport. Another factor helping to lessen annual growth inemissions is the switch to renewable energy sources, which has reduced the emissions intensity of the energy
mix annually since 2014.
The effect of an efficient energy supply (the ratio of primary energy needed to supply a unit of final energy
demand) has frequently changed, in some years helping to reduce annual emissions growth, while in others,
increasing emissions. This reflects yearly variations in the energy supply mix, such as changes in electricity
demand, which are often determined by factors such as weather.
FIGURE B4.4.1 • Decomposition of energy sector emissions, 2010–17
2000

1500

Mega-tonnes of CO2

1000

500

0

-500

-1000

-1500

2010

2011

2012

2013

GDP growth
Emissions intensity of energy supply

2014

2015

2016

2017

Improvements in primary energy intensity
Change in CO2 emissions from fuel combustion

Source: IEA, UNSD, and World Bank (see footnote 2).
Note: Countries covered are IEA member countries plus Argentina, Brazil, China, India, Indonesia, Russia, and South Africa—together
representing around 75 percent of global energy use.
CO2 = carbon dioxide; GDP = gross domestic product.
2000

1500

of CO2

CHAPTER1000
4 • Energy Efficiency

500

107

EMERGING TRENDS: DIGITALIZATION
Digitalization is rapidly transforming the energy sector, with possible implications for the achievement of SDG 7.3. Bygathering and analyzing data from a vast network of sources, digital technologies have the potential to optimize energy
production and consumption at a scale that would otherwise not be possible. With the proliferation of digital devices andlow-cost sensors, a wealth of data is now available to optimize energy use: linking data from smart meters, commuter
movements, mobile telephone networks, consumer purchasing decisions, social media, weather conditions, and more.
Digitalization makes end-use energy more efficient while distributing flexible load, generation, and storage. Bybroadening energy efficiency, digitalization contributes to system efficiency. Connected components of the energy
network increase end-use efficiency and in doing so support “prosumers” and integrate new sources of demand
response. Together they help make the system more efficient (IEA 2019a).
Although a complete accounting of digitalization is still uncertain—along with its promise of energy efficiency—
research suggests global potential. IEA estimates suggest that in the building sector, digitalization could cut totalenergy use by 10 percent by 2040, creating a cumulative energy savings of 234 exajoules—equivalent to more thanhalf the final demand consumed globally per year (IEA 2019a). Some models of urban transport suggest that digital
innovations such as teleworking, shared mobility, and connected and autonomous vehicles could reduce transportcarbon emissions by more than 50 percent in 2050 compared to business-as-usual emissions (ITF 2019).
It is important to note, however, that digitalization also poses risks. For example, the rapidly shifting transportlandscape (e.g., ride-hailing and micromobility) creates uncertainty around net energy use. Depending on which effects
dominate, models estimate that digitalization and automation trends could have a range of different effects on final
transport energy demand. Optimistic scenarios in which efficiencies are maximized could halve transport energy use
compared with current levels; pessimistic scenarios see transport demand doubling (Waduda, MacKenzie, and Leiby2016). Smart policies are therefore key to ensuring that digitalization leads to a more energy-efficient and sustainableenergy system (see below).

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POLICY RECOMMENDATIONS AND
CONCLUSIONS

R

ecent shortfalls in energy intensity—below rates that would meet SDG target 7.3—will require strengthened
government policies on energy efficiency. Decades of global experience demonstrate that well-designed and-implemented energy efficiency policies can deliver a range of benefits beyond energy and emissions savings.
Governments can realize these benefits through straightforward policy decisions.
Strong policy action is also vital to signal to investors that energy efficiency is a long-term priority, which will create
more certainty for investors and catalyze the transformative investments needed to return the world to a path leading
to the fulfillment of SDG target 7.3.

ENERGY EFFICIENCY POLICY
Governments have several policy tools for increasing energy efficiency, including regulatory instruments that mandate
minimum efficiency levels in buildings, appliances, vehicles, and industry; fiscal or financial incentives to increase
the financial viability of installing energy-efficient equipment; and information programs to help energy users makeeducated decisions. Here, we describe some options and policies.29
Analysis of energy use covered by regulatory instruments30 shows that only about one-third of use is covered bymeasures that mandate energy savings (Figure 4.10, left). Not coincidentally, policy coverage is highest in countries
that have made the most progress in lessening their energy intensity since 2010, such as China, Japan, and the UnitedStates.
FIGURE 4.10 • Growth in energy use covered by mandatory efficiency policies globally, 2010–17 (left), and2017 coverage in the 10 countries with the highest total primary energy supply (right)
35%
Japan

Final energy use covered (%)

30%

China
United States

25%

Canada20%

Germany
United Kingdom

15%

France
10%

Italy
India

5%

Mexico
0%

2010

2011

2012

Source: IEA 2019a.

2013

2014

2015

2016

2017

0%

10%

20%

30%

40%

50%

60%

70%

Final energy use covered (%)

29
More information and examples can be found in IEA’s Global Policies Database (https://www.iea.org/policies), the World Bank’s Regulatory Indicators for Sustainable Energy (RISE) (https://www.worldbank.org/en/topic/energy/publication/rise---regulatory-indicators-for-sustainable-energy), theGlobal Status Report of Renewable Energy Policy Network for the 21st Century (REN21), or the forthcoming recommendations of IEA’s Global Commission for Urgent Action on Energy Efficiency.
30
This metric reflects: the energy use of appliances, equipment, and vehicles required to comply with Minimum Energy Performance Standards(MEPS) before being sold; the energy use of buildings that were constructed or renovated in accordance with a mandatory building energy code; andthe energy use of industrial firms or sectors that are required by law to meet energy efficiency improvement targets.

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109

Minimum Energy Performance Standards (MEPS) are a proven tool in policy making. Introducing MEPS would be one
way to expand mandatory policies covering more products in more sectors globally. Mandatory MEPS have proven to
be cost-effective; evaluations show that benefits outweigh any additional costs by a factor of 3 to 1 (as in the Technology
Collaboration Programme on Energy Efficient End-Use Equipment, 4E-TCP [IEA 2016]). To date, over 80 countries haveadopted MEPS, covering more than 50 different types of technologies in different economic sectors; yet despite theirbenefits, MEPS are still absent in many jurisdictions.
Well-designed MEPS programs can include features that encourage energy efficiency well beyond the minimum
standards and drive innovation among equipment manufacturers to improve the competitiveness of industries andeconomies.
Japan, for example, encourages companies to compete with one another to obtain the official “Top Runner” label.
Consumers know this label confers a “best in class” energy efficiency rating. The program covers everything frompassenger cars to refrigerators. Performance standards are dynamic, so every few years the most efficient devices
are set as the new standard for everyone to meet (METI 2015). In operation since 1999, Top Runner has increased
the international competitiveness of Japanese companies and given consumers access to efficient and highly costeffective equipment. The program also reduced oil imports by more than 220,000 barrels in 2015 (METI 2015).
Government actions to reduce the cost of energy-efficient equipment include economic incentives such as grants
or loans. But bulk procurement policies are another tool for easing the cost of energy efficiency investments. Bulk
procurement has governments leveraging their considerable purchasing power to procure energy-efficient services or
products. Bulk procurement creates economies of scale, cuts the costs of services and products, and in some cases
fosters new or spin-off markets.
India, for example, is procuring millions of efficient lights through a national program called Unnat Jyoti by Affordable
LEDs for All (UJALA), which has already delivered more than 300 million lamps across India.31 Although the program
receives no public subsidy, consumers are able to pay for the lamps partly up front and partly out of the ongoingsavings. The purchasing power of the large program means that consumers pay only Rs. 70 (USD 1) for an energyefficient light-emitting diode (LED) bulb, well below the market price.

POLICIES FOR LEVERAGING DIGITAL TECHNOLOGIES TO SCALE UP EFFICIENCYEmerging digital technologies could be harnessed to make them more energy efficient so they do not simply add to
global energy demand. But this would require concerted policy action across several fronts. IEA’s Readiness for Digital
Energy Efficiency policy framework (IEA 2019a) identifies eight principles for policy makers to consider when planningfor emerging digital technologies. Many of these principles would require energy policy makers to work closely with
their counterparts across the government to address complicated, cross-cutting issues such as data protection,
privacy, and access. The eight principles are as follows:1.

Improve access to energy-related data

2.

Ensure adequate protection for cyber security and data privacy

3.

Strengthen trust in digital technologies

4.

Ensure energy markets value the services provided by digital energy efficiency

5.

Ensure equitable access to digital technology and infrastructure

6.

Increase digital skills and plan for job market transformation

7.

Minimize negative environmental impacts

8.

Encourage technology and business model innovation

31

India’s UJALA program is described at https://eeslindia.org/content/raj/eesl/en/Programmes/UJALA/About-UJALA.html.

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Tracking SDG 7: The Energy Progress Report 2020

BOX 4.5 • MARKET DESIGN AND INCENTIVES FOR EFFICIENCY INVESTMENTS
In addition to applying the right mix of available efficiency policy instruments, policy makers may also need toconsider how the design of energy and power markets may create incentives and disincentives to efficiency
investments. With conducive regulatory frameworks, and opportunities to bid into capacity markets, forexample, policy makers have an opportunity to incentivize greater investments in energy efficiency
Light-emitting diode (LED) street lighting is a further example of how efficiency incentives may be affectedby power market design. Converting older street lighting technologies to LED can generate energy savingsof between 40 and 70 percent, not to mention additional maintenance savings and improved urban lighting.
Thanks to these large potential savings, LED projects can offer competitive and swift returns. In some countries,
however, municipal and other public lighting projects are not being deployed at scale due to energy market
distortions (which may have adverse effects not only on efficiency but also on supply quality and systemcosts). These may include the way in which electricity generators and network distribution companies are
regulated and compensated, for example, through obligated procurement or power purchase agreements witha regulated price for electricity set above competitive market rates. In cases where a utility operates street
lighting infrastructure, and in parallel obtains a fixed amount from municipalities for the electricity to operatethat infrastructure, there is little incentive for the utility to invest in conversion to LED lamps.
Policy makers wishing to address these kinds of distortions might consider regulation more aligned with market
mechanisms as well as with social, economic, and environmental objectives. In addition to delivering carbon
emission reductions and reducing consumer energy bills, such an approach can lower system costs, improve
quality of supply, and incentivize efficiency gains across the distribution network. It can also lessen risks and cuttransaction costs, creating a more attractive environment for efficiency investments.

ENERGY EFFICIENCY INVESTMENT
Annual global investments in energy efficiency have remained largely unchanged since 2015. Investments into energy
efficiency typically fall into one of the following four key areas:
1.

Incremental spending on more efficient technologies

2.

Project investments by energy service companies

3.

Green mortgages, green bonds, and property-based repayment schemes

4.

Climate mitigation investments by international financial institutions

In 2018, incremental efficiency investments across the buildings, transport, and industry sectors stood at USD 236
billion, representing a growth rate of less than 1 percent compared to average annual investment between 2015 and2017 (Figure 4.11). While declining slightly in 2018, the buildings sector consistently receives the highest share—nearly
60 percent—of total investments. Industrial energy efficiency investments increased in China by 12 percent and in Indiaby 5 percent in 2018, but have continued to decline in the United States since 2015. Transport efficiency investments
increased only slightly in 2018, and mainly in freight, while sales of less-efficient light-duty trucks increased (IEA 2019a).
Deploying readily available efficiency technologies is one of the most cost-effective means of saving energy while
reducing emissions and achieving wider SDG objectives. At current levels, however, the world is not investing enoughin efficiency, suggesting a major missed opportunity. Unlocking the full potential of efficiency would require current
annual investment levels to double by 2025, and double again between 2025 and 2040, according to IEA (2018)
analysis.

CHAPTER 4 • Energy Efficiency

111

FIGURE 4.11 • Energy efficiency investment by region (left) and sector (right), 2018

Shares of investments in energy efficiency

100%
Industry

15%

80%

Transport

26%

60%

USD 239 billion
40%

20%

Buildings

59%

0%

2014

2015

Other

2016

Europe2017

North America

2018
China

Source: IEA 2019a.
HVAC = heating, ventilation, and air conditioning.

4%

4%

3%

3%

2010-2017

1990-2010

Iran

Korea

CanadaBrazilGermany

Iran

Korea

CanadaBrazilGermany

Japan

-2%

Russia

-2%

India

-1%

United States

-1%

Japan

0%

Russia

0%

1%

India

1%

2%

United States

2%

China

Compound annual growth rate (%)

5%1990-2010

112

Gas

5%

China

Compound annual growth rate (%)

Coal

2010-2017

Tracking SDG 7: The Energy Progress Report 2020

CONCLUSIONST

he improvement rate for energy intensity has slowed over the past few years, falling below the annual 2.6 percent
initially projected as a prerequisite to reaching SDG target 7.3. The year 2017 saw a 1.7 percent improvementfrom 2016—the lowest since 2010. The average rate over that seven-year period, 2.2 percent, was better than
the 1.3 percent annual average of the previous decade, but still low enough to require an average rate of more than
3 percent every year through 2030 in order to meet the target of halving energy intensity by 2030. Early estimatesfor 2018 and 2019 suggest improvement rates of 1.3 percent and 2.0 percent, respectively, indicating that the slowing
progress since 2015 may be turning around.
The 3 percent target remains within reach, given substantial investment in cost-effective energy efficiency improvements
on a systematic scale. In addition to reducing emissions and mitigating global warming effects, improved efficiency
at this scale would be a key factor in achieving affordable, sustainable energy access for all. The recent slowdown
of intensity improvements, the potential opportunities for investment, and the pressing need for expanded accessall point to the need for urgent action by governments to enact policies that would foster rapid progress toward a
3 percent annual improvement.
Key to the progress some countries are making toward energy efficiency has been the decoupling of their economy
from their energy use. This is most noticeable in countries like Japan, where minimally energy-intensive sectors (e.g.,
the services sector) play a more prominent role in the economy than high-intensity sectors like heavy manufacturing.
Still, some developing economies are seeing similar trends as their economies grow and their service and low-intensity
manufacturing sectors pick up steam.
Every sector displays the trend toward slowing rates of intensity improvement, with the notable exception of transport,
where every segment of the sector aside from freight shows improved efficiency rates. Passenger transport, for one,has seen increased demand as the world’s growing middle class accelerates demand for personal vehicles and longdistance travel. This increase in demand has been offset, however, thanks to the strengthened efficiency standards
many countries have implemented since 2010.
Digitalization has also been an emerging trend reshaping the energy landscape and facilitating progress toward
improved energy efficiency. Wide-scale data collection, analysis, and utilization can help to optimize demand andconsumption at scale and improve energy efficiency at a systems level. Sector-specific digitalization solutions arealso having a marked effect on energy efficiency. Some applications for the urban transport sector, for example, could
achieve a 50 percent reduction in carbon emissions by 2050 against business-as-usual rates. This burgeoning trend is
not exempt from risks, however. In addition to the opportunities to optimize efficiency, digitalization also can improveaccess to energy and in some cases drive up demand. It would be essential for governments to seriously consider thistrend when developing policies to ensure that the more optimistic scenarios end up dominating the landscape.
National and subnational governments have an array of policies to help them meet their energy efficiency goals.
A number of successful, implemented policies exist in various forms around the world, including energy efficiency
standards, financial incentives, market-based mechanisms, capacity-building initiatives, and regulatory changes. Allof them encourage investment in efficiency measures and rebalance energy markets in favor of cleaner, more efficient
operations.
The world has all the technology and resources it needs to double the rate of energy efficiency improvement by 2030,
over the rate observed between 1990 and 2010. The slowing rates of improvement and investment point to a major
missed opportunity for the global community. Making energy efficiency measures a priority in policy and investment
over the coming years can help the world achieve SDG 7.3, improve economic development, and ensure universal
access to clean, efficient energy.

CHAPTER 4 • Energy Efficiency

113

METHODOLOGY
Total primaryenergy supply(TPES) inmegajoules (MJ)

This represents the amount of energy available in the national territory during the reference period. It
is calculated as follows: Total primary energy supply = Primary energy production + Import of primaryand secondary energy – Export of primary and secondary energy – International (aviation and marine)
bunkers – Stock changes. (The definition is consistent with International Recommendations for Energy
Statistics).
Data sources: IEA Energy Balances, supplemented by UNSD for countries not covered by IEA.

Gross domestic
product (GDP)in 2011 U.S.
dollars (USD) atpurchasing power
parity (PPP)Primary energy intensity
in MJ/USD(2011)
PPP
Primaryenergyintensity
MJ/
Primaryenergyinintensity
USD (2011)
in MJ/USD(2011)PPP
PPP

Primary energy intensity
Averageannualrate
Primaryenergyintensity
inAverage
MJ/USD(2011)
PPP
annualrate
ofimprovement
ininof
MJ/USD(2011)
PPP
improvement
in energy
energy intensity
intensity(%)(%)
Averageannualrate ofimprovement in energy
intensity (%)

Total final energy
consumption
Averageannual(TFEC)
inrate
MJ of

Averageenergy
annual intensity
rate ofIndustrial
improvement
in energy
improvement
in energyin
MJ/USD(2011)
intensity(%) PPP
intensity
Industrial
energy(%)
intensity
in MJ/USD (2011) PPP
Value added in USD(2011) PPP

Services energy intensity
in MJ/USD (2011) PPP
Services energy intensity
Industrial
energyIndustrial
energyintensity
in MJ/USD(2011)
PPP
Industrial
energyinintensity
intensity
in MJ/USD(2011)MJ/
PPP
in MJ/USD(2011)PPP
PPP
USD (2011)
Agriculture energy
intensity in MJ/USD(2011) PPP
Agriculture
energyServices
energyintensity
in
MJ/USD
Services
energyinintensity
intensity
MJ/
Services
energyintensity(2011)PPPin MJ/USD(2011)PPP
PPP
USD (2011)
in MJ/USD (2011) PPP
Passenger transportenergy intensity in
MJ/passenger-kilometer
Passenger transport
Agriculture energy
Agriculture
energyenergyintensityinintensity in MJ/USD
114
intensity
MJ/USD
MJ/passenger-kilometer(2011)inPPP(2011) PPP
Freight transport energy
intensity in MJ/tonne-km

Sum of gross value added by all resident producers in the economy plus any product taxes and minus
any subsidies not included in the value of the products. It is calculated without making deductions fordepreciation of fabricated assets or for depletion and degradation of natural resources. GDP is measured
in constant 2011 USD PPP.

𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)
𝐺𝐺𝐺𝐺𝐺𝐺 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒
Ratio between
TPES𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
and GDP is=measured
in MJ2011
per USD(2011) PPP. Energy intensity (EI)𝐺𝐺𝐺𝐺𝐺𝐺 (𝑈𝑈𝑈𝑈𝑈𝑈
𝑃𝑃𝑃𝑃𝑃𝑃)
indicates how much energy is used to produce one unit of economic output. A lower ratio indicatesthat lessenergyTPES
isTPES
used
toGDP
produceoneunit inof MJ
economic
output.
Ratio
betweenGDPismeasured
in MJ
per
USDPPP.
(2011)
PPP.intensity
Energy(EI)
intensity (EI) indicates how
Ratio
betweenandandis measured
per
USD(2011)
Energymuchenergyis usedto produce
one unitoneof uniteconomic
output.
A lower
indicates
how muchenergyis used to produceof economic
output.
A lowerratio
ratio indicatesindicates that less energy is
Energyanimperfect
as ofchangesare output.
affected by other factors other than energy
usedtointensity
produceone
unitofindicatoreconomic
output.
that
lessenergyisis usedtoproduce
one unit
economic
efficiency,
particularlychangesin the structure
economic
activity.
Energyintensity
is animperfectindicatorofaschangesare affected by other factors other than energy
efficiency,
particularlychangesin thestructure
economic
activity.
Energy intensity
is an imperfectindicator
as changes
areofaffectedby otherfactors other than energy
Calculatedparticularly
using compound
annualrateof(CAGR):
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(𝑀𝑀𝑀𝑀)
efficiency,changesin thegrowth
structure
economic activity.
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)
Calculatedusing compound
rate (CAGR):
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =annual growth
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖= 𝐺𝐺𝐺𝐺𝐺𝐺 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)B
𝐺𝐺𝐺𝐺𝐺𝐺(𝑈𝑈𝑈𝑈𝑈𝑈
2011
𝑃𝑃𝑃𝑃𝑃𝑃)
Calculated using(@AD@B) annual growth rate (CAGR):
𝐸𝐸𝐸𝐸@Acompound
C and GDP
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶= > TPES− 1 (%)
Ratio
betweenismeasured
in
MJ
per
USD
(2011) PPP. Energy intensity (EI)𝐸𝐸𝐸𝐸TPES
Ratio between
Band GDP is measured in MJ per USD (2011) PPP. Energy intensity (EI)
@B
indicates
howmuchenergyisusedtoproduceone
unitof
economic
A lower ratio indicates(@AD@B)
𝐸𝐸𝐸𝐸@A energy is used to produce one unit of economic output.
Where: how
indicates
output. A lower ratio indicates
Where:> much
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶
=
−
1 (%)
that
less
energyisCused to
produce
one unit of economic output.
𝐸𝐸𝐸𝐸
isenergyintensity
in
year
t1
that
less
energyis used to in
produce
one unit of economic output.
𝐸𝐸𝐸𝐸@Bintensity
EI @Aisenergyyear t1
𝐸𝐸𝐸𝐸t2@B is energy intensity in year t2
Where:
Energyintensityintensity
is an imperfectindicator
EIt1 is energy
in yeart2 as changes are affected by other factors other than energy
Energyintensityintensity
is an imperfectas changes are affected by other factors other than energy
𝐸𝐸𝐸𝐸
in year in
t1indicator@A is energy
efficiency,
particularlychangesthe structure
economic
activity.in
Negativevaluesrepresent
decreases(orofenergyintensity
is used to
Negativevaluesrepresent
decreases(or improvements)
in energy(lessenergy is(lessusedenergy
toefficiency,
particularlychangesin the structure
ofimprovements)
economic
activity.intensity
𝐸𝐸𝐸𝐸
intensity
in yeart2@B is energy
produceoneunitunitof economicor perunit ofwhile
activity),
while
positive
numbers indicate increases in
produce oneof economic
outputoutput
or per unitof activity),
positive
numbers
indicate
Calculated
compoundannualrate(CAGR):
energyintensity(moreenergyis usedtoproduceoneoneunit
ofofeconomic
outputorunit of activity).
increases
inusingenergyintensity(more growthenergyisusedto produce
unit
economic
outputperperCalculated
using
compoundannualgrowthrate(CAGR):
Negativevaluesrepresent
decreases(or improvements)
in energy
intensity(less energy
is or
used
to
unit
of
activity).
produceone
unitof
economic
output
or
per
unit
of
activity),
while
positive
numbers
indicate
B
Sum of energy consumption
by the different end-use sectors, excluding nonenergy uses of fuels. TFEC
B(@AD@B)
𝐸𝐸𝐸𝐸
increases
energyintensity(moreenergy inis usedto producesectors:
one unit ofindustry,
economictransport,
output or per
isbrokenindown
energydemandthe following
residential, services,@A into> 𝐸𝐸𝐸𝐸@AC (@AD@B) − 1 (%)
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶=
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇
agriculture,andothers.−It1excludes
marineand(𝑀𝑀𝑀𝑀)
aviation bunkers, except at the world level
unitof activity).
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶= >𝐸𝐸𝐸𝐸(%)= international@B C
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
𝐸𝐸𝐸𝐸@B
where
in the transport
sector. 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
Where: it is included
Where:
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)
𝐸𝐸𝐸𝐸@A is energy intensity in year t1
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖=
𝐸𝐸𝐸𝐸
energy𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒
intensity
in yearBalances,
t1 industry
Datasources:
IEA Energy
supplemented
by UNSD
forpercountries
notPPP.
covered by IEA.
@A is
Ratio
betweenindustry
TFEC
andvalue added,
in MJ
USD𝑃𝑃𝑃𝑃𝑃𝑃)(2011)𝐸𝐸𝐸𝐸
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣measured
𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈
2011@B is energy intensity in year t2
𝐸𝐸𝐸𝐸@B is energy intensity in year t2
Data
source:World𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
Development
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒= Indicators.

Value added is the net output of a sector after adding up all outputs and subtracting intermediate
Data sources:
IEA
EnergyBalances
andWorld
Development
value
added).
Negative
represent
decreases(or improvements)
in energy
intensityusedassets
toRatio
betweenindustry
TFEC
and industry
value
added, measured
in MJ(forper(less
USD(2011)isPPP.
inputs.
Itvalues
is calculated
without
makingdeductions
forIndicators
depreciation
ofenergy
fabricatedor depletion and
Negative values represent decreases (or improvements) in energy intensity (less energy is used todegradationof ofnaturalresources.
Theunitindustrial
originvaluenumbers
added isdetermined by the International
produce one unit
economic
output or perof activity),
whileofpositive
indicate
produce one
unit of economic
output or per
unit𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
of 3.
activity),𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇
while positive
numbers indicate
Standard
Classification,
increases
inIndustrial
energyintensity(more energy
is usedto produceIndicators
one(𝑀𝑀𝑀𝑀)
unit of(foreconomic
output or per
Data sources:
IEA Energy
Balancesand revisionWorld
Development
value added).

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖= energy is used to produce one unit of economic output or perincreases
in𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒energy intensity
(more
unit
of activity).
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)

unit ofsource:
activity).World Development Indicators.
Data
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖= services value𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(𝑀𝑀𝑀𝑀)
Ratio between
services
TFEC andadded
measuredin 2011
MJ
per𝑃𝑃𝑃𝑃𝑃𝑃)
USD (2011) PPP.
𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎(𝑈𝑈𝑈𝑈𝑈𝑈
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(𝑀𝑀𝑀𝑀)
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)
𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼
𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎(𝑈𝑈𝑈𝑈𝑈𝑈
2011 𝑃𝑃𝑃𝑃𝑃𝑃)
Data sources:
EnergyBalances
andWorld
Development
Indicators
Ratio
between IEA
services
TFEC
and services
value
added measured
in MJ(forpervalue
USDadded).
(2011) PPP.
Ratio
betweenindustry
TFEC
andindustryvalue
added,
measured
in
MJ
per
USD
(2011)
Ratio
betweenindustry
TFEC
and industry
value measured
added, measured
in MJ
perPPP.
USD (2011) PPP.
Ratio between
industry
TFEC
and industry
value added,
in
MJ
per
USD
(2011)PPP.
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇
Data sources: IEA Energy Balances and World Development
Indicators(for(𝑀𝑀𝑀𝑀)
value added).
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =Data sources:
IEA
EnergyBalances
and𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴World
Development(for value
added).
𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣Indicators
𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈2011
𝑃𝑃𝑃𝑃𝑃𝑃)Data
sources:
IEA
EnergyBalancesand World
Development(forvalue added).
Data sources:
IEA
EnergyBalancesand World
Development
IndicatorsIndicators(for value added).
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(𝑀𝑀𝑀𝑀)(𝑈𝑈𝑈𝑈𝑈𝑈
Ratio between 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒agriculture𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
TFEC and=
agriculture
value added
measuredper USD(2011) PPP.
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣
𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎
𝑃𝑃𝑃𝑃𝑃𝑃)𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(𝑀𝑀𝑀𝑀) in MJ 2011
𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆
𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎Indicators(𝑈𝑈𝑈𝑈𝑈𝑈 2011
𝑃𝑃𝑃𝑃𝑃𝑃)added).
Data sources:
EnergyTFEC
Balances
World𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣
Development(forMJvalue
Ratio
between IEA
agriculture
and andagriculture
value added measured
inper USD (2011) PPP.
Ratio
betweenservices
TFEC
and services
valuemeasured
added measured
in MJ
per USD
Ratio between
services
TFEC
and services
value addedin MJ per USD(2011)
PPP. (2011) PPP.
Ratio between services TFEC and services value added
measuredin MJTFEC
per USD(2011) PPP.
Passenger
transport(MJ)
Data sources: IEA Energy Balances and World Development
Indicators(for value
added).
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖= Development Indicators (for value added).
Datasources:
IEA Energy
Balancesand World
Data sources:
IEA
Energy Balancesand World
Development
Indicators (forevalue
Passenger-kilomet
rs added).
Data sources: IEA Energy Balances and World Development Indicators (for value added).
Passenger transport TFEC (MJ)
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 final𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)
Ratio between𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡
passenger transportenergy =consumption
and passenger
Passenger-kilomet
erstransport activity
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =measuredin MJ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒
per passenger-kilometers.
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)
Ratio between passenger transport final energy consumption and passenger transport activity
SDG 7: The Energy Progress Report 2020
Data between
source:
IEA
Mobility
Model.and agriculture value added measured in Tracking
Ratio
agriculture
TFEC
MJ per USD(2011) PPP.
measuredin MJ
perpassenger-kilometers.
Ratio between agriculture TFEC and agriculture value added measured in MJ per USD (2011) PPP.
Freight transport
TFEC (MJ)
Data sources:
IEAMobility
Energy Model.
Balances and World Development
Indicators(for value added).
source: IEA
𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹ℎ𝑡𝑡
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖= Development Indicators (for value added).
Datasources:
IEA Energy
Balancesand World
Tonne-kilometers

𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)
Ratio between services TFEC and services value added measured in MJ per USD (2011) PPP.
Ratio between services TFEC and services value added measured in MJ per USD (2011) PPP.
Ratio between services TFEC and services value added measured in MJ per USD (2011) PPP.
Data sources: IEA Energy Balances and World Development Indicators (for value added).
Data sources: IEA Energy Balances and World Development Indicators (for value added).
Data sources: IEA Energy Balances and World Development Indicators (for value added).
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (𝑀𝑀𝑀𝑀)𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(𝑀𝑀𝑀𝑀)𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎(𝑈𝑈𝑈𝑈𝑈𝑈
2011 𝑃𝑃𝑃𝑃𝑃𝑃)𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇(𝑀𝑀𝑀𝑀)𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =Agriculture energy
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑈𝑈𝑈𝑈𝑈𝑈 2011 𝑃𝑃𝑃𝑃𝑃𝑃)
Agriculture
energy𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴
𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣
𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎(𝑈𝑈𝑈𝑈𝑈𝑈
2011 𝑃𝑃𝑃𝑃𝑃𝑃)
intensity
in MJ/USD
Agriculture
energyAgriculture
energyRatio between agriculture TFEC and agriculture value added measured in MJ per USD (2011) PPP.
intensity
in PPP
MJ/USD(2011)
intensity
inMJ/
intensity in MJ/USD
Ratio between
agriculture
TFECTFEC
and agriculture
value added
measuredin MJ per USD(2011)
Ratio
betweenagriculture
and agriculture
value
added measured
in MJ
perPPP.
USD (2011) PPP.
(2011)
PPP PPP
Ratio between
agriculture
TFEC and agriculture
value added
measuredin MJ per USD(2011)PPP.
USD(2011)(2011)
PPP
Data sources: IEA Energy Balances and World Development Indicators (for value added).
Data sources:
IEA
EnergyBalancesand World
Development
IndicatorsIndicators(for value added).
Datasources:
IEA
EnergyBalancesand World
Development(for value added).
Data sources:
IEA
EnergyBalancesand World
Development
Indicators (for value added).
Passenger transport TFEC (MJ)
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = Passenger transport TFEC (MJ)
Passenger-kilometers (MJ)
transport TFEC
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = Passenger
Passenger
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =Passenger-kilometers
Passenger transport
Passenger-kilomet
erstransport
energyPassenger
transport
energyintensity
inRatio between passenger transport final energy consumption and passenger transport activity
Passenger
transport
intensity
in MJ/
Ratio
betweenpassenger
transport
final
energyconsumption
andpassenger
transport activity measured
energyintensity
inRatio between
passenger
transport final energy consumption and passenger transport
activity
MJ/passenger-kilometermeasuredin MJpassenger
per passenger-kilometers.
energyintensity inpassengerRatio
transport final energy consumption and passenger transport activity
in
MJbetween
perinpassenger-kilometers.
MJ/passenger-kilometermeasuredMJ
perpassenger-kilometers.
kilometer
MJ/passenger-kilometermeasured in MJ per passenger-kilometers.
Data source:
Mobility
Model.
Data
source:IEA
IEA
Mobility
Model.
Data source: IEA Mobility Model.
Data source: IEA Mobility Model.
Freight transport TFEC (MJ)
Freight transport energy
Ratio between
freight 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒transport 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
final energy=consumption
and activity
measured in MJ per tonne𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹ℎ𝑡𝑡
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡
Freighttransport
TFEC
Freight transportenergyintensity
in MJ/tonne-km
Tonne-kilometers (MJ)
Freighttransport
TFEC(MJ) in MJ per tonneFreight transportenergy Ratio
𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹ℎ𝑡𝑡
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖=
kilometers.
betweenfreighttransport
final
energyconsumption
andactivity
measured
Freighttransport
intensity
in MJ/tonne-km
𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹ℎ𝑡𝑡
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒final𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖=
Tonne-kilomet
ersmeasured
Ratio
betweenfreight transportenergy consumption
and activity
in MJ per tonneintensity
in MJ/tonne-km
Tonne-kilometersenergyintensity in kilometers.
Ratio between freight transport final energy consumption and activity measured in MJ per
kilometers.
Data source: IEA Mobility Model.
MJ/tonne-km
tonne-kilometers.
Data source: IEA Mobility Model. 1
Data source:
Mobility
Model.
1
Residential TFEC (MJ)
Data
source:IEA
IEA
Mobility
Model.
1
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖= Residential TFEC (MJ)𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑚𝑚A )Residential energy 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 =Residential TFEC (MJ) A
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅
𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 (𝑚𝑚 ) A
𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖=
intensity in MJ/unitof floor
Residential
energy𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅
𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎building(𝑚𝑚 ) floor area.
Residential
energyRatio between residential TFEC and square meters of𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓
residential
Residential
energyarea
intensity
in MJ/unitinofMJ/unit
floor
intensity
Ratio
betweenresidential
TFEC
andsquaremetersofresidentialbuilding
floor buildingarea.
intensityin
MJ/unit
of
floor
Ratio
betweenresidential
TFEC and square meters of residential
floor area.
area
of floor area
Ratio
residential
Data between
source: IEA
MobilityTFEC
Model.and square meters of residential building floor area.
area
Data
source:IEA Mobility
Model.Model.
Datasource:IEA Mobility
Data source: IEA Mobility Model. 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐, 𝑜𝑜𝑜𝑜𝑜𝑜, 𝑎𝑎𝑎𝑎𝑎𝑎 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝑔𝑔𝑔𝑔𝑔𝑔
𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸=
𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜
𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑜𝑜𝑜𝑜𝑜𝑜, 𝑎𝑎𝑎𝑎𝑎𝑎
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶, 𝑜𝑜𝑜𝑜𝑜𝑜,
𝑎𝑎𝑎𝑎𝑎𝑎𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐,
𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛
𝑔𝑔𝑔𝑔𝑔𝑔𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 𝑔𝑔𝑔𝑔𝑔𝑔
𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 = 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐, 𝑜𝑜𝑜𝑜𝑜𝑜, 𝑎𝑎𝑎𝑎𝑎𝑎 𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛 𝑔𝑔𝑔𝑔𝑔𝑔
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶,
𝑜𝑜𝑜𝑜𝑜𝑜,𝑎𝑎𝑎𝑎𝑎𝑎𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛
𝑔𝑔𝑔𝑔𝑔𝑔𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖
𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒=
Fossilfuel
Fossil fuel electricity
𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶,oil,𝑜𝑜𝑜𝑜𝑜𝑜,
𝑔𝑔𝑔𝑔𝑔𝑔𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 and the fossil
Ratio of the electricity output from fossil fuel (coal,and𝑎𝑎𝑎𝑎𝑎𝑎gas)𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛𝑛
fired power
generation
generation
efficiency (%) Ratio
Fossilfuelelectricity
electricity
ofelectricity
theelectricity
outputfromfossilfueland(coal,
oil,
and
gas)
fired power
generationand the fossil fuelgeneration
fuel
TPES
input
to output
power fromgeneration.
Ratio
of
the
fossilfuel(coal,
oil,
gas)
fired
power
generationand thefossilFossilfuelelectricity
generation
efficiency (%)
(%)
TPES
input
to power
generation.
Ratio
of
the
electricity
outputfromfossilfuel(coal,
oil,
and
gas)
fired
power
generation
andthefossilefficiency
generation efficiency (%) fuel TPES input to power generation.
fuel
input
to Energy
power generation.
DataTPES
source:
IEA
Balances.
Data source: IEA Energy Balances.
Data source: IEA Energy Balances.
Data
source:IEA Energy Balances.
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡
𝑎𝑎𝑎𝑎𝑎𝑎 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙
𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡 𝑎𝑎𝑎𝑎𝑎𝑎 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙=(%)
𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃
𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡
𝑎𝑎𝑎𝑎𝑎𝑎𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙
𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸
𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙(𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸
𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜
𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚+ 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸
𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶 + 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖)
𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙=(%)(𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 + 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶 + 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖) (%)=
Power
transmission(𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 + 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 𝐶𝐶𝐶𝐶𝐶𝐶 + 𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸𝐸 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖)
Powertransmission
and Where:
Where:and distribution
Electricity
losseselectricity
transmission
and distribution
distribution
losses(%)
Electricity losses
areareelectricity
transmission
and distribution
losses; losses;
Power transmission
andWhere:
losses (%)
Power transmission
Where:
Electricity
outputis electricity
outputandfromdistribution
main
activity
producerelectricity
plants;anddistribution
losses (%) and Electricity
lossesare mainelectricity
losses;Electricity
outputmain
istransmission
electricity
outputfrommainactivity
producerelectricity
plants; anddistribution losses (%) Electricity
Electricity
lossesareelectricity
transmission
andcombined
distribution
losses;Electricity
outputCHP
is electricity
outputfromheat
andelectricity
power
plants.
outputmain
isCHP
electricity
outputfrommainactivity
producerplants;andplants.
Electricity
outputis electricity
outputfrom combined
heat andpower
Electricity
outputmain
is electricity
outputmain activity
producerElectricity
outputCHP
is electricity
outputfromfrom
combinedheat andpowerelectricity
plants. plants; andElectricity
outputCHP
is electricity
output from combined heat and power plants.
Data source:
source:
IEA
EnergyBalances.
Data
IEA
EnergyBalances.
Data source: IEA Energy Balances.
IEA
Balances
database, https://www.iea.org/data-and-statistics/.
DataWorldsource:Energy
IEA Energy
Balances.
Services energy intensity
Services
energyintensity
in MJ/USD(2011)
PPP
Services
energyintensity
in MJ/USD (2011) PPP
in MJ/USD (2011) PPP

Data sources citedin this table

UNSD Energy Balances database, https://unstats.un.org/unsd/energystats/.
World Development Indicators database, http://datatopics.worldbank.org/world-development-indicators/.
IEA Mobility Model.

CHAPTER 4 • Energy Efficiency

115

REFERENCES
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Programs.” International Energy Agency Technology Collaboration Programme on Energy Efficient End-Use
Equipment (4E-TCP), Paris. https://www.iea-4e.org/files/otherfiles/0000/0377/4E_2016_S_L_Report_
Final.pdf.
IEA (2017), Market Report Series: Energy Efficiency 2017, Paris: IEA. https://webstore.iea.org/market-report-seriesenergy-efficiency-2017-pdf.
IEA (2018), Energy Efficiency 2018: Analysis and Outlooks to 2040, https://www.iea.org/reports/energy-efficiency-2018.
IEA (2019a), Energy Efficiency 2019, http://www.iea.org/efficiency2019/.
IEA (2019b), Global EV Outlook 2019: Scaling up the Transition to Electric Mobility, https://www.iea.org/reports/globalev-outlook-2019.
IEA (2019c), World Energy Balances 2019, https://www.iea.org/data-and-statistics/.
IEA (2020), Global Energy Review 2019: The latest trends in energy and emissions in 2019, https://www.iea.org/
reports/global-energy-review-2019.
ITF (International Transport Forum). 2019. ITF Transport Outlook 2019. Paris: ITF. https://doi.org/10.1787/transp_
outlook-en-2019-en.
METI (Japan Ministry of Economy, Trade, and Industry). 2015. Top Runner Program. Tokyo: METI. https://www.enecho.
meti.go.jp/category/saving_and_new/saving/data/toprunner2015e.pdf.
REN21 (Renewable Energy Policy Network for the 21st Century). 2019. Renewables 2019: Global Status Report. Paris:
REN21. https://www.ren21.net/gsr-2019/chapters/chapter_02/chapter_02/.
Waduda, Z., D. MacKenzie, and P. Leiby. 2016. “Help or Hindrance? The Travel, Energy, and Carbon Impacts of Highly
Automated Vehicles.” Transportation Research Part A: Policy and Practice 86 (April): 1–18.

116

Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 5: OUTLOOK FOR
SDG 7

CHAPTER 5

Photo: Shutterstock

OUTLOOKFOR SDG 7

MAIN MESSAGESOutlook for progress toward 2030: At the current rate of progress, the world is not on track to achieve
Sustainable Development Goal 7 (SDG 7). In this chapter, forward-looking scenarios are used to outline how theenergy system could further support the achievement of global climate and sustainable development goals. The
Stated Policies Scenario of the International Energy Agency (IEA) shows that current and planned policies will not
be enough to meet the goals; in fact, under this scenario, none of the target is reached by 2030. IEA’s Sustainable
Development Scenario lays out a pathway to put the world’s energy system on track to achieve the SDG targets
most closely related to energy (those in SDG 3.9, SDG 7, and SDG 13).32 For renewables, the Transforming Energy
Scenario 2030 of the International Renewable Energy Agency (IRENA) also presents a possible way to achieve thegoal of substantially increase renewable energy.

Outlook for access to electricity: Recent progress was mixed, as is the outlook to 2030: under IEA’s Stated
Policies Scenario, around 620 million people would still lack access to electricity in 2030. Thanks to well-designed
policies, the countries of Developing Asia are expected to expand electricity access to 98 percent of the region’s
population by 2030. In Sub-Saharan Africa, Ethiopia, Ghana, Kenya, Rwanda, Senegal, and South Africa shouldreach universal access. Nonetheless, without further efforts, 36 percent of the population of Sub-Saharan Africa
would be without access in 2030 if current and planned policies are continued. Decentralization is an importantpart of the answer. IEA’s most recent analysis of Africa demonstrates that decentralized solutions constitute theleast-cost way of providing access to more than half of the population who must gain access by 2030 to meet thetarget. The challenge boils down to expanding access to those living close to the central grid, while deploying inparallel decentralized systems to connect those living farther away—particularly in countries where access is least
advanced.



Outlook for access to clean cooking solutions: If clean cooking remains low on the political agenda, 2.3 billion
people in 2030 will still be relying on traditional uses of biomass, kerosene, or coal for cooking, according to
IEA’s Stated Policies Scenario, with dramatic consequences for the environment and for the health of womenand children. The acute challenge in Developing Asia and Sub-Saharan Africa is to understand how cultural,
economic, and social factors combine to slow progress. A possible path forward lies in building on successfulpolicies implemented in countries such as Ethiopia, Ghana, and India, and on the innovations observed elsewhere,
to support the deployment of clean fuels and technologies, notably liquefied petroleum gas (LPG), natural gas,
improved biomass cookstoves and innovative, renewables-based electric stoves and alcohol stoves.



Outlook for renewable energy: The IEA and IRENA scenarios both conclude that solar photovoltaic (PV) andwind will account for most renewables-based electricity generation by 2030. The IEA’s Sustainable Development
Scenario further shows that intensified policy support and cost reductions could push the share of modern
renewables in total final energy consumption (TFEC) to 23 percent, in which case renewables would supply
around 50 percent of electricity generation. In IRENA’s Transforming Energy Scenario, the rise in renewables by2030 is slightly higher, reaching 28 percent of TFEC and 57 percent of electricity generation. While renewables
would climb to around 50 percent or more of electricity generation under both the IEA and IRENA scenarios, more
dedicated efforts are needed to boost the penetration of renewables in transport and heating.

32
Most of this chapter is based on results from IEA’s World Energy Model (IEA 2019e) and from analysis in the World Energy Outlook (IEA 2019a).
Some of the geographical groupings in this chapter, unlike foregoing chapters, are those used in the World Energy Outlook. “Developing Asia” refers to
non-OECD Asia

119



Outlook for energy efficiency: Recent estimates indicate that annual improvements in global energy intensity is
low for 2018 (1.3 percent) and 2019 (2.0 percent), moving the world further from achieving SDG 7.3. For example,
the efficiency improvement in transport slowed in 2018, in large part because global consumer preferences shifted
toward heavier SUVs. As a result, the new annual rate of improvement required from 2017 to 2030 to achieve
the target would be over 3 percent, while IEA’s Stated Policies Scenario shows that the expected improvement
resulting from current and planned policies would only be around 2.3% annually from 2017 to 2030. With the rightpolicies in place, IEA’s Sustainable Development Scenario shows that an annual average rate of improvement of
3.6 percent between 2017 and 2030 is nonetheless possible. The building sector holds large potential for energy
savings from efficiency improvements. It is the locus of more than 40 percent of the needed savings in energy
demand by 2030 under the Sustainable Development Scenario, compared with the Stated Policies Scenario.

Additional investments and fuel savings: IEA and IRENA’s scenarios estimate that achieving SDG 7 would
require annual investments by 2030 of around $680 billion to renewable energy (IRENA and IEA scenarios),
around $45 billion going to energy access and $625 billion to energy efficiency (IEA scenario). Furthermore, aredirection of investment from fossil fuels to renewables is necessary to unlock the capital needed to put the worldback on track to a sustainable future. In total, savings of up to USD 220 billion per year in fossil fuels investment
could be achieved under the Sustainable Development Scenario. IRENA’s Transforming Energy Scenario suggeststhat USD 10 trillion would have to be redirected from fossil fuels and related infrastructure.

International public financial flows to developing countries in support of clean and renewable energy:
While the bulk of investment in the energy transition has and would continue to come from private sources, publicfinance will play a significant enabling role to spur investment. Tracking of progress toward SDG indicator 7.A.1
performed by IRENA and the Organisation for Economic Co-operation and Development (OECD) shows thatinternational public financial flows to developing countries in support of clean and renewable energy have grownby around USD 1.6 billion per year since 2010, reaching USD 21.4 billion in 2017.33 Although this increase in publicfinancial flows to renewables is promising, only 12 percent of the flows reached the least-developed countries in
2017.



SDG 7 and emissions: The energy system is strongly linked with greenhouse gas emissions, and the achievementof SDG 7 is critical to the attainment of SDG 13, which aims to slow climate change. Scenarios from both IEA and
IRENA show that greater policy efforts in renewable energy and energy efficiency (complemented by several othertechnologies) account for most of the energy-related reductions in CO2 emissions needed to realize the Paris
Agreement.

33
The figures are drawn from the Renewable Energy Public Investments Database, a joint OECD/IRENA database on international financial flows
to developing countries in support of clean and renewable energy. https://www.irena.org/Statistics/View-Data-by-Topic/Finance-and-Investment/Renewable-Energy-Finance-Flows120

Tracking SDG 7: The Energy Progress Report 2020

T

his chapter describes the results of global modeling exercises undertaken to determine whether current policy
ambitions are sufficient to meet the SDG 7 targets, and to identify what additional actions might be needed. It
also analyzes what investments are required to achieve the goals, including an update on SDG indicator 7.A.1
on international financial flows to developing countries in support of renewables. It finishes by highlighting the links
between the energy system and emissions of greenhouse gases, suggesting that tackling both through well-guided
actions will be critical to progress toward SDG 13. Scenarios for the various targets are taken from IEA’s flagshippublication, World Energy Outlook (IEA 2019a). With respect to the renewable energy target, scenarios are also derived
from IRENA’s Global Renewables Outlook: Energy Transformation 2050 (IRENA 2020d).
IEA’s Stated Policies Scenario (referred to in earlier IEA publications as the New Policies Scenario) reflects the impact
of existing policy frameworks and announced policy intentions. Its utility is to hold up a mirror to the plans of today’s
policy makers and elucidate their consequences for energy use, emissions, and energy security. The policies coveredby the scenario span a broad range, starting with Nationally Determined Contributions under the Paris Agreement. In
practice, the bottom-up modeling implied by the scenario involves a great deal of detail at the sectoral level, including
pricing policies, efficiency standards and schemes, electrification programs, and specific infrastructure projects.
IEA’s normative Sustainable Development Scenario34 describes an integrated least-cost pathway allowing the world’s
energy system to deliver on energy-related SDGs: to ensure universal access to affordable, reliable, sustainable, andmodern energy services by 2030 (SDG 7); to substantially reduce the air pollution that causes deaths and illness(SDG 3.9); and to take effective action to combat climate change (SDG 13). This scenario takes the SDG outcomesas its point of departure, working backward to set out what would be needed to achieve those outcomes in a costeffective way. By 2030, under this scenario, universal access to both electricity and clean cooking is achieved; modern
renewables reach 23 percent of total final energy consumption, more than doubling today’s share; energy efficiency
aims of SDG target 7.3 are exceeded, with average annual improvements in global energy intensity accelerating to
3.8 percent annually between 2019 and 2030; and the global temperature increase over preindustrial levels is held well
below 2°C.
Two IRENA scenarios sharpen the picture. IRENA has explored global energy development pathways to 2030 and
2050 from two perspectives. The first is an energy pathway shaped by current and planned policies (the Planned
Energy Scenario); the second, a cleaner, climate-resilient pathway based largely on a more ambitious, yet achievable,
uptake of renewable energy and energy efficiency measures (the Transforming Energy Scenario).35

34
More information on the IEA Sustainable Development Scenario can be found at: https://www.iea.org/reports/world-energy-model/sustainable-development-scenario.
35
More information on the IRENA Transforming Energy Scenario can be found at: https://www.irena.org/publications/2020/Apr/Global-Renewables-Outlook-2020.

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121

THE OUTLOOK FOR ELECTRICITY ACCESS
WHERE ARE WE HEADED?
Thanks to recent progress in several countries (chapter 2), the outlook for access to electricity indicates continued
progress to 2030 but without achieving universal access. The number of people still lacking access to electricity in
2030 is expected to shrink under the current and planned policies mapped out in the Stated Policies Scenario to around
620 million (roughly 7 percent of the global population), 530 million of them in Sub-Saharan Africa. SDG target 7.1
remains within reach, and policies implemented in several countries have put them on track to achieve universal
access, but the same cannot be said for many Sub-Saharan African countries.
Strong performance should put Developing (non-OECD) Asia on track to reach an access rate of 98 percent by 2030
(Figure 5.1). Bangladesh, India, Indonesia, and the Philippines are well on track to reach full access before 2030. Greater
efforts are needed in Afghanistan or Mongolia, however, if the region is to achieve 100 percent access in 2030. Central
and South America is projected to continue its steady progress, moving to 99 percent in 2030, with Haiti the only majorcountry in the region to have a substantial unelectrified population.
FIGURE 5.1 • Electricity access rates and distribution of population still lacking access in 2030, by region,
under Stated Policies Scenario
Rate of access by region

Distribution of population without access by region
Rest of world

4%

Developing Asia

Developing Asia

11%
Central andSouth America

Sub-Saharan Africa

North Africa

Sub-Saharan Africa

85%
Middle East

0%

20%

40%

60%

80%

100%

Source: IEA 2019a.

The situation is improving in Sub-Saharan Africa, where effective policies should allow Ethiopia, Ghana, Kenya, Rwanda,
Senegal, and South Africa to reach full access by 2030 under the Stated Policies Scenario (IEA 2019b). For the region
as a whole, the access rate is projected to rise to around 64 percent, though high rates of population growth mean thatthe number of people without access would still be about 530 million in 2030 under the Stated Policies Scenario. There
would be almost 20 countries where less than half of the population has access, and 10 where less than one in four hasaccess. Among the latter group are Chad, the Democratic Republic of Congo, Malawi, Niger, and Somalia. As a result,
Population gaining access each year from 2019 to 2030of access in
gains
Sub-SaharanAfrica by
by 2030,85 percent of the global population without access would Breakdown
be concentrated
theinregion.
By 2040,that sharetechnology under Sustainable Development Scenario
would be more than 90 percent.
100
90
80
70
60

122
50

40
30

Stand-alone
systems
Tracking SDG 7: The Energy Progress Report 202026%

On-grid43%

North Africa

Sub-Saharan Africa

85%
Middle East

HOW TO BRIDGE THE GAP
0%

20%

40%

60%

80%

100%

To bridge the gap and connect the remaining 620 million people projected by the Stated Policies Scenario to be without
access in 2030, the connection rate would have to triple from its current level—to nearly 90 million a year between
2019 and 2030 (figure 5.2). Most of the acceleration would have to happen in Sub-Saharan Africa, as discussed in theprevious paragraph. Certain countries would have to scale up efforts, notably the Democratic Republic of Congo, Niger,
Nigeria, Sudan, and Uganda, which together are home to half of the regional population lacking access in 2030 under
the Stated Policies Scenario.
FIGURE 5.2 • Projected gains in access to electricity by region and technology, 2019–30
Population gaining access each year from 2019 to 2030

Breakdown of access gains in Sub-Saharan Africa bytechnology under Sustainable Development Scenario

100
90
80
70
60

Stand-alone
systems

50

26%

40

On-grid

43%30
20
Mini-grids

10

31%

0
Stated Policies Scenario

Sub-Saharan Africa

Sustainable Development
Scenario (full access)Developing Asia

Other

Source: IEA 2019a, 2019b.

Policies that promote centralized and decentralized solutions in parallel are crucial to unlocking electricity access.
Geospatial analysis developed by IEA identified decentralized systems as the least-cost option for more than half ofthe electricity connections (representing nearly 440 million people) that would have to be made in Sub-Saharan Africa
if the region were to achieve universal access by 2030. Decentralized solutions (largely based on renewables) can beadapted to conditions in remote rural areas, where around 80 percent of the population without access in Africa would
be concentrated in 2030.36 If deployed carefully, such systems can complement the grid, providing energy services
immediately and preparing the way for grid expansion in the future. Parallel efforts should be made to increase thecentral grid’s density so as to connect nearby households and, where feasible, to extend it to reach large population
centers. Capitalizing on the coverage of its main grid, Kenya implemented the Last Mile Connectivity Project, which
has connected an average of one million households annually since 2015. Direct investment in the existing electricity
network is also essential to improve and maintain energy services, increase trust in the central network, and raise thefinancial and operational performance of utilities.
Unlocking this potential for progress requires well-defined and transparent government planning that integrates all
solutions, assesses the related investment needs, and provides clarity about the roles of all actors. Cross-sectoralplanning and coordination to support the deployment of energy-efficient appliances and productive uses of energy will
also be necessary. Several countries—among them Ethiopia, Ghana, Rwanda, and Senegal—developed comprehensive,
long-term strategies of the sort needed to provide modern energy services to everyone in Sub-Saharan Africa incoming years.

36
In collaboration with the KTH Royal Institute of Technology, IEA developed a geospatial model to identify optimal country-by-country electrification solutions, taking into account local geography, population density, technology costs, existing infrastructure, and resource availability. The analysis
covered 44 countries of Sub-Saharan Africa, with a deep focus on 11: Angola, Côte d’Ivoire, Democratic Republic of Congo, Ethiopia, Ghana, Kenya,
Mozambique, Nigeria, Senegal, South Africa, and Tanzania. Maps illustrating the results for the 11 focus countries can be found in the country profiles of
the Africa Energy Outlook 2019 (IEA 2019b) and online at https://www.iea.org/reports/africa-energy-outlook-2019.

CHAPTER 5 • Outlook for SDG 7

123

THE OUTLOOK FOR ACCESS TO CLEAN
COOKING FUELS AND TECHNOLOGIESWHERE ARE WE HEADED?
The outlook for clean cooking is of the utmost concern; the world is far off track from achieving universal access toclean cooking solutions. In 2030, under the Stated Policies Scenario, 27 percent of the world’s population would still
be deprived of access to clean fuels and technologies for cooking. This means that, with population growth, around
2.3 billion people would still be relying on traditional uses of biomass, kerosene, or coal as their primary cooking
fuel. It also means that premature deaths from household air pollution would remain roughly at today’s level. Forest
degradation, sometimes leading to outright deforestation, is yet another grave consequence of the unsustainable
harvesting of fuelwood, chiefly for the production of charcoal to be used in cities.
In 2030, the population without access to clean cooking solutions is split almost equally between Developing Asia and
Sub-Saharan Africa. In Developing Asia, the projected access rate in 2030 is 70 percent, leaving some 1.2 billion people
without access (figure 5.3). Great progress is projected in India, which is expected to shrink the population without
access to 500 million in 2030, achieving an access rate of 67 percent. This outcome is the result of the government’s
determination to promote clean cooking through the Pradhan Mantri Ujjwala Yojana (PMUY) scheme, which offers free
LPG stoves and cylinders to women in poor households. The government is also extending and improving urban gas
infrastructure.
FIGURE 5.3 • Rates of access to clean cooking fuels and technologies in 2030
Access to clean cooking in theStated Policies Scenario

Demand for cooking energy, by fuel type,under Sustainable Development Scenario

Other

Developing Asia

6%
Natural gas

Central andSouth America

24%
Improvedbiomass
cookstoves

Sub-Saharan Africa

34%

LPG

North Africa

26%
Electricity

Middle East

0%

10%
20%

40%

60%

80%

100%

Source: IEA 2019a.
LPG = liquefied petroleum gas.

In Sub-Saharan Africa, greater efforts to reduce reliance on traditional uses of solid biomass for cooking would bring
the rate of access to 34 percent by 2030. Nevertheless, because of rapid population growth, more than 970 million
would remain without access in 2030. In some countries such as Ethiopia, Côte d’Ivoire, Ghana, Kenya, and Tanzania,
ambitious policies will bend the curve and shrink the numbers without access, providing clean cooking solutions toaround half of their population by 2030. For example, Ethiopia’s government launched phase two of its National Biogas
Program in
2017; the program aims
to provide at least 180,000 people
with biogas digesters by 2022.
Historical
STEPS
SDS
25%

25%

124
20%

20%

Tracking SDG 7: The Energy Progress Report 2020

Traditional uses ofbiomass and ICSHOW TO BRIDGE THE GAP
Under the Sustainable Development Scenario, every household in the world would have access to clean cooking by
2030, an achievement that would require providing access to a total of 2.5 billion people. Clean cooking solutions cut
household air pollution and improve health, particularly for women and children. In view of the stakes, efforts to deploy
effective technologies need to be moved up on the international political agenda. Engaging with local women in thedesign, uptake, and sale of clean cookstoves is a key part of successful implementation.
How best to expand access to clean cooking depends on a variety of cultural and economic factors, notably theavailability of resources and infrastructure. Under IEA’s Sustainable Development Scenario, more than half of the
population gains access through LPG in urban areas, while advanced cookstoves are a determining factor in rural
areas. Other fuels—such as electricity, biogas, ethanol, and natural gas—also play a growing role in reaching universal
access.
Providing access to clean cooking solutions for all by 2030 and action to mitigate climate change are complementary
objectives. The dramatic acceleration in deployment of clean cooking solutions needed to reach universal accessby 2030 requires all currently available and scalable fuels and technologies, with LPG and natural gas playing animportant role in transitioning to decarbonized cooking solutions. While the range of uncertainty is high, analyses showthat providing access to all and moving away from traditional uses of biomass could support the fight against climatechange, considering the high levels of methane, black carbon, and nitrous oxide emissions resulting from incomplete
combustion of biomass, as well as the associated deforestation (IEA 2018).

CHAPTER 5 • Outlook for SDG 7

125

THE OUTLOOK FOR RENEWABLE ENERGY
WHERE ARE WE HEADED?
SDG target 7.2 envisions a substantial increase in the share of renewable energy in the energy mix. Although aquantitative objective is not specified, long-term scenarios charting various paths for the energy sector can assist
in benchmarking progress. IEA’s Stated Policies Scenario and IRENA’s Planned Energy Scenario both plot where theworld is headed under existing policy frameworks and stated policy plans.
The outlook for renewables under IEA’s Stated Policies Scenario has been steadily improving in all regions in response
to supportive policies and falling technology costs. The share of all renewables (including traditional uses of biomass)is projected to rise above 21 percent of TFEC by 2030, from 17 percent in 2017, while that of modern renewables would
increase to 15.5 percent in 2030 from 10.5 percent in 2017.37 IRENA’s Planned Energy Scenario, by contrast, showsslightly higher growth in the share of modern renewables in TFEC—from 10 percent in 2017 to 17 percent in 2030.
The use of renewables to generate electricity has grown the fastest in recent years, and the various scenarios predictthat will continue. According to IEA’s Stated Policy Scenario, renewables-based generation is expected to overtake
generation from coal in the mid-2020s and, by 2030, to account for 37 percent of all electricity generated. Of therenewable sources of electricity, solar PV is projected to grow by an average of 13 percent each year through 2030,
putting it on a pathway to rival wind as the largest source of renewable-based generation. According to IRENA’s Planned
Energy Scenario, the supply of renewable electricity would reach 38 percent by 2030. Direct uses of renewables havenot enjoyed the same level of policy support and cost reduction as the renewables used to generate electricity.38 As aresult, projected growth is slower for the direct uses of renewables such as biofuels, solid biomass, and solar thermal,
with their shares in meeting demand for heat and transport fuels growing to 10 percent and 5 percent respectively by2030, up from 8 percent and 3 percent in 2017, according to IEA.39

HOW TO BRIDGE THE GAP
Insights from IEA’s Sustainable Development Scenario
The increases in the use of renewable energy that are likely to occur under current and stated policies fall short of what
is required to achieve global goals for climate protection and sustainable development. IEA’s Sustainable Development
Scenario charts a path to achieve these goals, and renewables play a major role, with their use growing twice as fast
as under current and stated policies. Under this more ambitious scenario, modern renewables are expected to reachnearly 23 percent of TFEC in 2030 (figure 5.4).
The share of renewables-based electricity generation increases most rapidly, doubling its current share to just under
50 percent by 2030, 11 percentage points higher than under the Stated Policies Scenario. The promising outlook forelectricity generated from renewables is aided by strong policy support toward decarbonization of the power sector
and continued declines in the cost of key technologies, notably solar PV, batteries, and wind. At the global level,
electricity generation from renewable sources more than doubles from today’s level to over 15,000 terawatt-hours(TWh) by 2030, more than triple the amount of electricity generated in the United States today from all sources.

37
Because traditional uses of biomass are linked with significant pollution and deforestation, and because the use of biomass for cooking must be
scaled back to achieve other SDGs, this section focuses on modern renewables.
38
Renewable energy may be used in a relatively direct way to provide an energy service (such as solar power for heat) or indirectly from renewables-based electricity or renewables-based heat, which is then used to provide an energy service (such as to power heat pumps or electric vehicles, orto supply district heating).
39“Heat” in this chapter refers to the amount of energy consumed to produce heat for industry, buildings, and other sectors. All of these will be referred to hereafter simply as “heat.” They are not equivalent to heat as a final energy service, which refers to the energy available to end users to satisfy
their needs, after taking into account transformation losses.

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Tracking SDG 7: The Energy Progress Report 2020

FIGURE 5.4 • Share of modern renewables in total final energy consumption under the Stated Policies andSustainable Development Scenarios, 2010–30
Historical

SDS

STEPS

25%

25%

20%

20%

15%

15%

Traditional uses ofbiomass and ICS
Solar thermal andgeothermal
Renewable district heat
10%

10%

Renewable electricity
5%5%Modern bioenergy

2010

2015

2020

2025

2030

2020

2025

2030

Source: IEA 2019a.
Note: “Traditional uses of biomass” refers to the use of local solid biomass resources by low-income households that do not have access to modern
cooking and heating fuels or technologies.
STEPS = Stated Policies Scenario; SDS = Sustainable Development Scenario; ICS = Improved cookstoves.

IEA’s Sustainable Development Scenario also sees a greater electrification of energy use, with electricity meeting23.7 percent of TFEC in 2030, compared with 21.6 percent under the Stated Policies Scenario. Increased electrificationof transport and heating complements the direct use of renewables in efforts to decarbonize energy use. Direct
renewables, principally biofuels, increase to 10 percent their share of demand for transport-related energy; combinedwith growing electrification, renewables’ share in transport rises to 12 percent. Although light-duty vehicles are on apathway to decarbonization by 2030, challenges remain to decarbonize trucking, aviation, and shipping. The use ofrenewables to provide heat also grows considerably under the Sustainable Development Scenario, with the direct
use of bioenergy, solar thermal, and geothermal energy expanding by an average of 3 percent annually to reach a
combined share of 14 percent of total energy demand for heat in 2030. When the increased electrification of energy
demand is factored in, the total share of renewables in heating rises to 19 percent by 2030.
The share of traditional uses of biomass falls to around 5 percent of TFEC by 2030 under the Stated Policies Scenario.
Under the Sustainable Development Scenario, traditional uses of biomass are completely phased out, as developing
countries replace them with more modern and efficient fuels and technologies.
Across regions, variations in energy policy, socioeconomic trends, and natural-resource endowments result in differing
growth trajectories for renewables. Developing economies account for two-thirds of the growth in electricity generation
through 2030 under both the Stated Policies and Sustainable Development scenarios, with developing economies in
Asia, led by China and India, representing half of the increase.
Under the Stated Policies Scenario, the outlook for electricity generation from renewable sources ranges from
9 percent in the Middle East and 16 percent in North Africa, at the low end, to well over 70 percent in Central and SouthAmerica, where hydropower is the backbone of the power mix. Under the Sustainable Development Scenario, theshare of renewable electricity generation increases in every region across the globe, approaching or surpassing halfof all electricity generation by 2030 in several regions. Indonesia and other Southeast Asian economies see the mostsignificant increase in the share of renewables in electricity generation under the Sustainable Development Scenario,
led by growth in wind and solar PV.

CHAPTER 5 • Outlook for SDG 7

127

FIGURE 5.5 • Change in consumption of modern renewable energy, by region under the Stated Policies andSustainable Development Scenarios, 2018-30
600

50%Solar thermal andgeothermal

500

40%
Renewable district
heat

400

Mtoe

30%
Renewable electricity

300
20%
200

Modern bioenergy
10%

100

Asia PacificNorth
America

Central &South
America

EuropeEurasia

Africa

SDS

STEPS

SDS

STEPS

SDS

STEPS

SDS

STEPS

SDS

STEPS

SDS

STEPS

SDS

STEPS

Share in TFEC
(right axis)

Middle East

Source: IEA 2019a.
Note: Modern bioenergy excludes traditional uses of biomass.
Mtoe = million tonnes of oil equivalent; STEPS = Stated Policies Scenario; SDS = Sustainable Development Scenario; TFEC = total final energy
consumption.

Insights from IRENA’s Transforming Energy Scenario
The increase in renewable energy use under IRENA’s Planned Energy Scenario, a pathway set by current and planned
policies, falls short of what is required to achieve global climate objectives and SDG 7. In it, the share of modern
renewables would reach only 17 percent in 2030. By contrast, under the agency’s more ambitious Transforming Energy
Scenario for 2030, the share of modern renewable energy in TFEC would rise steeply, from around 10 percent in 2017
to 28 percent by 2030 (Figure 5.6). The increase would proceed from a combination of factors—chief among themsignificant growth in the supply of renewables-based electricity, increased electrification of end uses, greater direct
use of renewable energy, and improved energy efficiency.
Transport

3%

16%
At a sectoral level, the buildings
sector would show the highest share of renewable energy by 2030. Renewables would
56%
raise their share of TFEC from the 2017 levels of 35 percent (when traditional uses of biofuels are included) or 13 percent(excluding traditional usesof biofuels) to 40 percent by 2030 (with all traditional uses of biofuels phased out).
13%
Industry29%

The next-largest renewables share would be in industry (including blast furnaces62%
and coke ovens), where renewables
would increase from a 13 percent share in 2017 to 29 percent by 2030 (of which 17 percent would be direct applicationofBuildings
renewable energy, 11 percent electricity, and 1 35%
percent district heat). The industrial sector offers great potential
40%
for improving efficiency through advances in industrial processes, demand-side management solutions,
81% recycling ofmaterials, and better waste management.
TFEC

17%

28%
Transportation would have the lowest shareof renewables in 2030 but the greatest growth, climbing to 16 percent
66%
of the sector’s final energy consumption by 2030, from just 3 percent in 2017. Energy
efficiency is as critical for the
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
transport sector as for the previous two; it can be achieved through the adoption of low-carbon
technologies,
as wellas through modal shifts—for example,2017
to innovative
mobility
services
such
as
car
sharing,topublictransport,
or from(total)2030 (total)
2050
airplanes to trains for short and medium-distance trips.

128

Tracking SDG 7: The Energy Progress Report 2020

FIGURE 5.6 • Share of renewable energy in total final energy consumption under IRENA’s Transforming
Energy Scenario, in total and by major end uses
3%

Transport

16%

56%

13%

Industry

29%

62%
35%

Buildings

17%

TFEC
0%

10%

40%

81%

28%

20%

66%

30%

40%

2017 (total)

50%2030 (total)

60%

70%

80%

90%

2050

Source: IRENA 2020d.
Note: 2017 includes traditional uses of biofuels in the building sector and in TFEC. By 2030, all traditional uses of biofuels are phased out of the energy
supply.

Scaling up electricity from renewables is a prerequisite for decarbonizing the world’s energy system. Increasingly,
electrification based on renewables is seen as a major solution, and the contribution of renewable electricity will be
the single largest driver for change in the global energy transformation. IRENA’s Transforming Energy Scenario sets apathway to achieve, by 2030, a 57 percent share of renewables in the global power generation mix, up from 25 percent
in 2017 (Figure 5.7). The role of electricity as an energy carrier will also increase, growing from a 20 percent share of
TFEC to 29 percent share in the Transforming Energy Scenario in 2030, with gross electricity consumption increasing
50 percent between 2017 and 2030, from 25,600 TWh to 35,900 TWh.
Looking beyond 2030, IRENA’s Transforming Energy Scenario also outlines a pathway to 2050 (figure 5.6). In
it, electricity would become the central energy carrier, coming to account for nearly 50 percent of TFEC by 2050.
Simultaneously, gross electricity consumption would more than double from 2016 levels to 55,000 TWh in 2050.
FIGURE 5.7 • Share of modern renewables in electricity generation in 2017, 2030, and 2050
60,00050,000TWh40,00086% RE

30,00057% RE

25% RE

20,00010,0000

2017
Base year

2030

2050
Transforming Energy Scenario (TES)

Coal

Oil

Natural gas

Hydropower (excluding pumped)

Bioenergy

Solar photovoltaic

Wind onshore and offshore

Geothermal

Others (including ocean)

NuclearConcentrating solar power

Source: IRENA 2019

CHAPTER 5 • Outlook for SDG 7

4%

129

In this context, the most important synergy of the global energy transformation is the increasingly low cost of renewable
power technologies, combined with wider adoption of electricity for end-use applications in transport and heat.
Among all power generation sources, wind and solar PV would dominate global electricity generation and capacity
additions under IRENA’s Transforming Energy Scenario. By 2030, one-third of the world’s electricity would come fromsolar and wind power, increasing to almost 60 percent by 2050, with total installed wind and solar capacity exceeding
6,000 and 8,500 gigawatts, respectively, by 2050. However, while a 50 percent electricity share in TFEC is feasible by
2050, the other 50 percent, which cannot be electrified, must be decarbonized.
Each sector has options for decarbonization. The first option is energy efficiency, which includes advances in bothtechnical efficiency and behavior. Energy efficiency would also contribute (together with renewables and electrification)
to better energy intensity, predicted to increase by 3.2 percent each year through 2050 under the Transforming Energy
Scenario.
Reduced consumption of fossil fuels is the second option. Under the Transforming Energy Scenario, fossil fuels retain
a role in 2050, providing one-third of the energy supply. But global production of oil and coal would decline. Oil would
largely be used in industry for petrochemicals, as well as in aviation and shipping. Coal would be used only in industry(7 percent of TFEC), mostly for steel production. Production of natural gas would grow through the mid-2020s,
dropping by 2050 to two-thirds of the 2017 level. By 2050, natural gas would be the most widely used fossil fuel.
The third major decarbonization option involves indirect electrification (using hydrogen and synthetic fuels) and the
direct use of renewables, including bioenergy. Both would increase significantly. Liquid biofuels, in particular, would
play an important role in aviation and marine energy supply, and in providing heat for industrial processes. Hydrogenis also a promising energy carrier, complementing the direct use of electricity, which, under the Transforming Energy
Scenario, has the potential to supply 11.1 exajoules of global energy demand by 2030 (of which 3.2 exajoules would
be from renewable sources) and nearly 29 exajoules by 2050 (two-thirds from renewable sources). Other direct usesof renewables include geothermal and solar thermal heat; both of these heating technologies would contribute to thedecarbonization of heat supply in industry.

130

Tracking SDG 7: The Energy Progress Report 2020

THE OUTLOOK FOR ENERGY EFFICIENCY
60,000G

lobal energy intensity, measured by the ratio of primary energy demand to gross domestic product (GDP), is the
key indicator used to gauge global progress on energy efficiency. Global energy intensity reached 120 tonnes ofoil equivalent (toe) per thousand dollars (2010 PPP) of GDP in 2017, an improvement of only 1.7 percent over2016.40,000
The slowdown means that to achieve SDG target 7.3 (which calls for a doubling of the rate of global energy
intensity by 2030), annual improvements for 2018 forward would have to be around 3 percent, rather than the
86%
REat just
2.6 percent
originally required. Recent estimates show that the improvement for 2018 was evenlower,
30,0001.3 percent, pointing to a third consecutive year of slowdown in the rateof
improvement.
The
slowdown
likelyreflects
57% RE
weaker implementation of energy efficiency
policyandstrongdemandinenergy-intensive
economies
andsectors.
A
25% RE
clear20,000
example of the global slowdown in improvements can be seen in the transport sector, where heavier, less-fuelefficient SUVs are increasing their market share, not only in the United States and Europe, but also in emerging nations
such 10,000
as China, India, and South Africa.
TWh50,000

IEA’s Stated Policies Scenario assumes an annual efficiency improvement of just 2.3 percent between 2017 and 2030,
0accompanied by a steadyrise in global final energy consumption
to more than 11,600 million
2017
2030
2050 tonnes of oil equivalent
Base year
Transforming Energy Scenario (TES)
by 2030.
Coal efficiency is a cornerstone
Oil of IEA’s Sustainable
Natural gas Development
NuclearBy contrast, energy
Scenario. The accelerated
solar
power demand
Solar photovoltaic
Bioenergy
Hydropower(excluding
pumped)improvements in energy
efficiency
acrossall energy
end uses under
this scenario wouldConcentrating
cause global
energyOthers (including
ocean)
onshoreoffshore The adoption
Geothermal
to peak by 2025, Wind
followedbyand
a decline.
of the measures
outlinedin the scenario translates to energy
savings of 1,700 million tonnes of oil equivalent over the Stated Policies Scenario, overshooting SDG target 7.3. The
annual 3.6 percent improvement in energy intensity under the Sustainable Development Scenario between 2017 and2030 is obtained through a combination of well-implemented policies and regulations.

FIGURE 5.8 • Average annual improvement in primary energy intensity under the Stated Policies andSustainable Development scenarios, 2010–30
4%

3%

2%

1%

2010-1620172018(estimated)2019(estimated)

STEPS
2017-30

SDS
2017-30

Source: IEA 2019a, 2020
STEPS = Stated Policies Scenario; SDS = Sustainable Development Scenario.

More than 40 percent of the global savings in energy consumption achieved by 2030 under the Sustainable
Development Scenario compared with the Stated Policies Scenario stem from the buildings sector, where building
codes and energy efficiency standards for appliances and devices offer significant scope for improvement in mostregions. Industry is the second-largest potential source of savings, representing around 30 percent of the global total.
The gain would come from replacing outdated equipment, processes, and systems with more efficient versions. The
remaining savings in energy consumption are attributed to transport, where stricter fuel-economy standards andemissions restrictions, combined with a variety of measures to accelerate the uptake of electric vehicles, could reduce
global energy consumption by more than 20 percent by 2030.

CHAPTER 5 • Outlook for SDG 7

131

FIGURE 5.9 • Improvement in energy intensity by sector and region in the Stated Policies and Sustainable
Development Scenarios, 2018–30
40%
Passenger cars
Additional in SDS
STEPS

30%

Industry
20%

Additional in SDS
STEPS

10%
Residential buildings
Additional in SDS
STEPSAsia PacificNorth
America

Central &South
America

EuropeEurasia

AfricaMiddleEast

Source: IEA 2019a.
STEPS = Stated Policies Scenario; SDS = Sustainable Development Scenario.

Billion dollars (2018)

To realize the Sustainable Development Scenario, the world has to exploit the full potential for efficiency improvements.
Success will depend on a thorough understanding of global energy needs, as energy demand trends vary substantiallyfrom region to region, with sectors playing larger or smaller roles in country economies. There is no single solution
to apply across the board. In every region, it is essential to start with the sectors where demand is high and room for
improvement is greatest. For example, in Asia, the dominant sources of growth in energy demand is set to be industry
and transport—these are the sectors that will require the greatest policy attention. In most parts of Africa, by contrast,
1 400
efficient
urban planning and strict building codes would help reduce the rapidly rising demand for energy. In North
America and Europe, energy demand has been rising because of increased cooling needs in summer and heating needs
in winter, attention should be paid to improving the efficiency of cooling and heating systems. Global commitment to
1 300
achieve greater efficiency progress is nonetheless evident. At the United Nations Climate Action Summit in September
2019, 15 countries launched the Three Percent Club40 and announced plans to work together to drive a 3 percent
annual 1rate
200 of improvement in global energy intensity.
1 100

1 000

900

800
Sustainable
Development
Scenario
40
The Three Percent Club is a coalition of governments and supporting organizations committed to placing the world on a path to a 3 percent annual
improvement in efficiency. The target was based on IEA’s Efficient World Scenario, derived from the Sustainable Development Scenario. To support themember countries, the coalition leverages the combined global resources of the IEA, the SEforAll Energy Efficiency Accelerators and Hub, the Global Environment Facility, the UN Environment Programme, the European Bank for Reconstruction and Development, and the Energy Efficiency Global Alliance.
Key industry partners commit to provide technical, financial, and project support to the participating countries, acting through the Energy Efficiency
Global Alliance.
Stated Policies
Scenario

132

Electricity
accessCleancookingRenewableenergyEnergyefficiency

Tracking SDG 7: The Energy Progress Report 2020

40%
Passenger cars
Additional in SDS
STEPS

30%

INVESTMENT NEEDED TO ACHIEVE SDG 7
Industry
20%

Additional in SDS

I

n the Sustainable Development Scenario, total energy sector investments needed to achieve all
targets of SDG 7
STEPS
are estimated to average USD 1.36 trillion per year between 2019 and 2030 (Figure 5.10) (IEA 2019a). To achieve
universal access to energy would require investments of around USD 45 billion per year between 2019 and 2030. Of
these
10% investments, USD 40 billion would be required to attain universal access to electricity, or more than twice theamount observed in the Stated Policies Scenario. Significant scale-up of investment would be requiredin Sub-Saharan
Residentialbuildings
Africa, compared with that observed under current and planned policies, as it totals two-thirds of the additional
Additional in SDS
investment in electricity access.
Providing access to clean cooking facilities to all the population now without access would STEPS
require five times
Asia Pacificspelled
North
Central&Europe Scenario,
Eurasia
AfricaMiddle per year. Clean cooking needs
the investment
out in theStatedPoliciesor almost
USD 5 billion
AmericaSouth
to be placed higher on
the political
agenda so as to accelerate efforts to widenEast
access and take advantage of theAmerica
momentum achieved to date. The latest estimates (2017) show USD 32 million supporting access to clean cooking
in high-impact countries: Afghanistan, Bangladesh, China, Democratic Republic of Congo, Ethiopia, India, Indonesia,
Kenya, Democratic Republic of Korea, Madagascar, Mozambique, Myanmar, Nepal, Nigeria, Pakistan, Philippines,
Sudan, Tanzania, Uganda, and Viet Nam (SEforAll and CPI 2019). It is worth noting that total investment for accessto clean cooking represents less than 2 percent of the total annual energy sector investment under the Sustainable
Development Scenario.
FIGURE 5.10 • Additional annual direct investment needed to meet SDG 7 targets, 2019–30

Billion dollars (2018)

1 400

1 300

1 200

1 100

1 000

900

800
Stated Policies
Scenario

Electricity
accessCleancookingRenewableenergyEnergyefficiency

Sustainable
Development
Scenario

Source: IEA 2019a.
Note: Investments under the Stated Policies Scenario include investment in the power sector and additional investments in end-use efficiency.

Under the Sustainable Development Scenario, the bulk of the investment required for meeting SDG 7 needs to go to
renewable energy and end-use efficiency,41 accounting for around USD 690 billion and USD 625 billion respectively.
Compared to investments realized under current and planned policies, this represents an increase of almost USD 230
billion per year for renewables, principally going to renewables-based power, and of nearly USD 180 billion for efficiency,
the greater part of it going to more efficient buildings and transport. These additional capital investments nonethelessconceal a different approach to financing compared with the Stated Policies Scenario; they could be achieved through41
Renewable energy investments include investments in renewables power generation and grid integration costs. It also includes investments directly related to renewable energy capacity in industry and buildings end uses. Energy efficiency investments include those directly related to the efficiency of industry, buildings, and transport end uses.

CHAPTER 5 • Outlook for SDG 7133

a redirection of capital within the energy system. Indeed, the combination of lower energy use from efficiency
investment alongside greater shares of renewables leads to a reduction of investments into fossil fuel of more than
USD 220 billion per year, thereby demonstrating the economic viability of reaching the goals. All in all, the energy
system would see additional annual investments limited to USD 210 billion to follow the pathway of the Sustainable
Development Scenario relative to the Stated Policies Scenario.
Analysis performed for IRENA’s Transforming Energy Scenario suggests that investments of nearly USD 10 trillion
should be redirected from fossil fuels and related infrastructure to low-carbon technologies by 2030. Cumulative
investments in the energy system over the period to 2030, including infrastructure and efficiency, would be reaching
USD 60 trillion (Figure 5.11). Nearly USD 9.5 trillion of these investments would be needed to scale up renewable
power generation capacity through 2030. In annual terms this would imply doubling of investments in renewable
power generation capacity to USD 676 billion per year to 2030, compared with the USD 289 billion invested in 2018
(Frankfurt School–UNEP Centre/BNEF 2019). This would require a substantial investment. But leaving the energy
system untransformed would be costlier. IRENA has estimated that between now and 2030, every additional dollar
spent on the energy transformation would pay back between USD 2.5 and USD 7.5 in fuel savings, lower net energy
subsidies, and reduced health externalities.
FIGURE 5.11 • Cumulative investment in the energy system under the Transforming Energy Scenario,
2016–30
Hydrogen - electrolysers

Electrification of heatand transport

Power grids andenergy flexibility

Biofuels
production

0.2 trillion

CCS and others

0.2 trillion

1 trillion

4 trillion

Fossil fuels - supply

9 trillion

4 trillion

Renewables - end uses

Fossil fuels - power

1 trillion

2 trillion

Nuclear60

Renewables - power

0.4 trillion

USD trillion

9 trillion

Energy efficiency

29 trillion

Source: IRENA 2020d.
CCS = carbon capture and storage.

42

134

15/www.climateinvestmentplatform.com/.
https:/

10

15

Investment per project(millions of dollars)tional Financial Flows to developing countries(billions of dollars)

Scaling-up of renewable energy investments requires coordinated action on multiple fronts. One recent initiative tocoordinate action to mobilize renewable energy investment at the necessary scale is the Climate Investment Platform,
an inclusive partnership of public and private stakeholders.42 While the bulk of investment in the energy transition will
25
25
need to come from private sources, public finance will play a significant enabling role to spur investment. Greater andmore efficient risk-mitigation solutions by public institutions and financiers (including development finance institutions
and multilateral development banks) can scale up investment, in particular in developing countries (IRENA 2020c).
Included for the first time in Tracking SDG 7 is an overview of progress toward SDG indicator 7.A.1 on international
public financial
flows to developing countries in support of clean and renewable energy (box 5.1).
20
20

Tracking SDG 7: The Energy Progress Report 2020
10

BOX 5.1 • SDG INDICATOR 7.A.1 ON INTERNATIONAL PUBLIC FINANCIAL FLOWSTO DEVELOPING COUNTRIES IN SUPPORT OF CLEAN AND RENEWABLE ENERGY
SDG target 7.A envisions enhanced international cooperation to facilitate access to clean energy research andtechnology, including the enabling of investment in renewables, with SDG indicator 7.A.1 focusing on international
public financial flows to developing countries in support of clean and renewable energy.
Recent international public flows and trends
Between 2000 and 2017, developing countries received a cumulative sum of USD 138.9 billion (2017 PPP) in
financial flows in support of renewables. In 2017, these flows reached USD 21.4 billion—up 13 percent from 2016,
twice the amount recorded in 2010, and a 15-fold increase since 2000, reflecting the rapidly intensifying focus
on development aid for clean and renewable energy.
Hydropower receives almost half of 2017 flows
Of the accumulated USD 138.9 billion (2017 PPP) in support of renewables between 2000 and 2017, USD 64.5
billion went to hydropower projects, 27.8 billion to solar, USD 10.1 billion to wind, and USD 36.5 billion to otherenergy sources. After a few years of dominance by solar, hydropower was back to receiving the greatest share in
2017, at 46 percent, while solar projects received 19 percent, wind 7 percent, and geothermal 6 percent.
The scale of public investment projects also increased over the period, from an average of USD 10 million per
project in 2000–09 to USD 19 million over the four years from 2014 to 2017. From 2016 to 2017, project scale
grew the most for hydropower, with a two-fold increase from USD 53 million to USD 104 million per project.
During the same period, the scale of solar projects decreased from USD 25 to 13 million per project, windremained stable at USD 27 million per project, and geothermal inched up from USD 31 to 34 million per project.
The least-developed countries receive only small shares of 2017 flows
Although public financial flows grew after 2010 by an average of USD 1.6 billion per year, most of the growth was
not targeted to those most in need—the least-developed countries. Between 2000 and 2017, only 20 percent of
cumulative flows reached that set of countries. In 2017, the least-developed countries received USD 2.7 billion(12 percent of flows) and small island developing states less than USD 0.8 billion (4 percent of flows).
Out of 65 donors, four Asian donors committed 52 percent of the investments in 2017. The China Development
Bank and the Export-Import Bank of China led with USD 9.0 billion, with an average of USD 651 million per
project, followed by the Asian Development Bank (USD 1.1 billion) and the government of Japan (USD 1.0 billion).

CHAPTER 5 • Outlook for SDG 7

135

Energy efficiency

29 trillion

25

25

20

20

15

15

10

10

5

5

0

2000

2005

2010

2015

Multiple/other energy sources

Geothermal energy

Wind energy

Solar energy

Hydropower

Investment per Project

Investment per project(millions of dollars)International Financial Flows to developing countries(billions of dollars)

FIGURE B5.1.1 International financial flows to developing countries in support of clean and renewableenergy (at 2017 prices and exchange rates)

0

Source: Renewable Energy Public Investments Database.
Note: Figures in this box are drawn from the Renewable Energy Public Investments Database, a joint OECD/IRENA database on international
financial flows to developing countries in support of clean and renewable energy (https://www.irena.org/Statistics/View-Data-by-Topic/
Finance-and-Investment/Renewable-Energy-Finance-Flows).

136

Tracking SDG 7: The Energy Progress Report 2020

SDG 7 AND REDUCTION OF EMISSIONST

he current energy system produces numerous greenhouse gases, making the energy sector responsible foraround 75 percent of such emissions. Climate change mitigation is thus a mounting concern for the sector, andin 2020 countries will have to present revised and more ambitious commitments for the first time as a result of
the Paris Agreement, which was adopted in 2015.
The reductions in CO₂ emissions needed to realize the Paris Agreement will require a deep transformation across theenergy system. To understand the weight of each lever, the Sustainable Development Scenario assessed countryby-country pathways that could deliver these targets, depending on local policy preferences, costs, resources, andsocietal preferences. Efficiency and renewables would produce the greatest reductions, equivalent to 37 percent and32 percent respectively of the additional efforts required in the Sustainable Development Scenario relative to theStated Policies Scenario (Figure 5.12).
Energy efficiency is the primary “fuel” of choice in most regions owing to its cost-effectiveness; no pathway compatible
with the Paris Agreement can afford to leave it aside. It can drastically reduce the fuel intensity of energy service
demand in the buildings, industry, and transport end-use sectors. It is also central to reducing the peak load on the
power grid, leading to a decrease of the peaking capacity, which is often associated with higher-cost and more-carbonintensive technologies. While energy efficiency alone is insufficient, it is essential to attaining stable, energy-related
CO₂ emissions below 30 gigatonnes by around 2040.
FIGURE 5.12 • Additional reductions in CO2 emissions by measure under the Sustainable Development
Scenario relative to the Stated Policies Scenario
40
Stated Policies Scenario

37% Efficiency
Gigatonnes of carbon dioxide

30

32% Renewables
20

8% Fuel switching
3% Nuclear
9% CCUS
Sustainable Development Scenario

10

2010

2020

2030

2040

12% Other

2050

Source: IEA 2019a.
Note: Reduced thermal losses in power generation account for 15 percent of efficiency improvements.
CCUS = carbon capture, utilization, and storage.

CHAPTER 5 • Outlook for SDG 7

137

The second major contributor would be the increased deployment of renewables. Policies would be central tostrengthening the competitiveness of renewable technologies relative to fossil fuel power plants, capitalizing on
the cost reductions observed to date for solar and wind technologies. Measures supporting the integration ofrenewables into the energy system would complement cost reductions and tap into their huge potential. Any increase
in renewables should nevertheless be accompanied by the phaseout of inefficient fossil fuel power plants to reducethe carbon intensity of power generation. The contribution of renewables could go further than power systems andtargeted policies; their increased use for heating in industry and buildings as well as for transport (through advanced
biofuels) would offer major benefits.
These two technologies alone—energy efficiency and renewables—could account for almost 70 percent of the effort
needed to reach the targeted emissions pathway. Reaching sustainable development goals would also require a hostof other technologies and policies, from carbon capture utilization and storage (CCUS) to hydrogen. There is no single
or simple solution to reach the Sustainable Development Goals.
Similarly, IRENA’s Transforming Energy Scenario shows that annual energy-related CO2 emissions under current andplanned policies (the Planned Energy Scenario) are expected to remain flat, at 33 gigatonnes of CO2 per year in 2050.
However, under the Transforming Energy Scenario, emissions would be reduced by 70 percent by 2050, with continued
reductions thereafter, keeping the rise in global temperature to well below the 2°C climate goal. The Transforming Energy
Scenario analysis shows that the accelerated deployment of renewables, combined with extensive electrification andincreased energy efficiency, could achieve over 90 percent of the energy-related CO2 emissions reductions needed by
2050. Electrification with renewable power is key in lowering energy-related carbon emissions, together comprising
60 percent of the mitigation potential. If the additional reductions from direct use of renewables are considered, theshare increases to 75 percent, and to more than 90 percent when counting energy efficiency.

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Tracking SDG 7: The Energy Progress Report 2020

CONCLUSION

D

espite the great progress unlocked recently by innovative policies and technologies throughout the energy
sector, the world is not on track to reach SDG 7 under current and planned policies. Efforts need to be scaledup across all goals so sufficient progress can be made. Providing universal access to energy requires a greatly
accelerated pace of electricity connections in Sub-Saharan Africa. In parallel, access to clean cooking solutions needs
to be placed much higher on political agendas in the developing and emerging world. Commercially viable renewables,
especially for heat and transport, and renewed commitment to improving the coverage and stringency of efficiency
regulations are urgently needed. It is increasingly realized that universal energy access targets are unlikely to be met
without addressing the need for gender equality in energy access and in energy supply, whether in households or inbusinesses and energy companies.
A world on track to meet SDG 7 would deliver numerous socioeconomic benefits, which is why SDG 7 is central toachieving the other Sustainable Development Goals set out by the United Nations. In particular, energy and climate
goals are interlinked and complementary. Pushing renewables and energy-efficient technologies across the energy
system will play the main role in reducing greenhouse gas emissions as needed to meet the Paris Agreement.

CHAPTER 5 • Outlook for SDG 7

139

METHODOLOGY
IEA METHODOLOGY
The analysis presented in this chapter is based on results from the World Energy Model (WEM) and IEA analysis in theWorld Energy Outlook (WEO). A detailed documentation on the World Energy Model methodology can be found here.
The 2019 edition of WEO featured a special look at Africa. IEA updated and expanded its analysis of the continent’s
energy outlook in this year’s WEO. For the first time, models were developed for 11 selected Sub-Saharan countries, andthese models were fed into the WEM. The country models enabled us to produce comprehensive, data-rich profiles forthese countries and to draw implications for the continent as a whole.
IEA scenarios
The analyses shown above are built on two main scenarios described below. This page contains further details about
how these two scenarios are modeled:Stated Policies Scenario: The Stated Policies Scenario reflects the impact of existing policy frameworks andtoday’s announced policy intentions. Its aim is to provide a detailed sense of the direction in which existing policy
frameworks and today’s policy ambitions would take the energy sector out to 2040. Previously known as the New
Policies Scenario, it has been renamed in WEO 2019 to underline that it considers only specific policy initiatives
that have already been announced. The policies assessed in the Stated Policies Scenario cover a broad spectrum.
These include Nationally Determined Contributions under the Paris Agreement and much more besides. In
practice, the bottom-up modeling effort in this scenario requires a lot of detail at the sectoral level, including
pricing policies, efficiency standards and schemes, electrification programs, as well as specific infrastructure
projects. You can find more information about this scenario here.

Sustainable Development Scenario: The Sustainable Development Scenario is a forward-looking, normative
scenario, which describes an integrated, least-cost pathway for the world’s energy system to deliver on energyrelated SDGs: to ensure universal access to affordable, reliable, sustainable, and modern energy services by 2030
(SDG 7); to substantially reduce the household air pollution that causes deaths and illness (SDG 3.9); and to takeeffective action to combat climate change (SDG 13). It shows how the respective objectives can be reconciled,addressing potentially conflicting priorities so as to realize mutually supportive benefits. In this scenario, looking
toward 2030, universal access to both electricity and clean cooking is achieved; modern renewables reach21 percent of TFEC, more than doubling today’s share; the energy efficiency aims set in SDG target 7.3 areexceeded in the Sustainable Development Scenario, with average annual improvements in global energy intensity
accelerating to 3.4 percent annually to achieve critical energy sector objectives. You can find more information
about this scenario here.

Methodology for access to electricity and access to clean cooking
The projections presented in the WEO and in this chapter focus on two elements of energy access: a household having
access to electricity and to clean cooking facilities. These are measured separately. The IEA maintains databases onlevels of national, urban, and rural electrification rates; for the proportion of the population without clean cooking
access, the main sources are the World Health Organization (WHO) Household Energy Database and IEA’s Energy
Balances. Both databases are regularly updated and form the baseline for WEO energy access scenarios to 2040.
The projections shown in the Stated Policies Scenario take into account current and planned policies, recent progress,
as well as population growth, economic growth, urbanization rate, and the availability and prices of different fuels. In
the Sustainable Development Scenario, we identify least-cost technologies and fuels to reach universal access to bothelectricity and clean cooking facilities. For electricity access, this is done by incorporating a Geographic Information
Systems model based on open-access geospatial data, with technology, energy prices, electricity access rates anddemand projections from the WEM. This analysis has been developed in collaboration with the KTH Royal Institute ofTechnology, Division of Energy Systems Analysis (KTH-dESA) in Stockholm. For the Special Focus on Africa of WEO
2019 (IEA 2019b), IEA refined its geospatial estimation of the least-cost pathway toward universal access to electricity

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Tracking SDG 7: The Energy Progress Report 2020

by 2030, using latest WEM results and the latest version of the Open Source Spatial Electrification Tool (OnSSET)
developed by KTH-dESA.43 The results provide detailed coverage of 44 countries in Sub-Saharan Africa.
Further details about the IEA methodology for energy access projections are in this document.

METHODOLOGY FOR RENEWABLE ENERGY PROJECTIONS
The annual updates to WEO projections reflect the broadening and strengthening of policies over time, including
for renewables. The projections of renewable electricity generation are derived in the renewables sub-module of theWorld Energy Model, which projects the future deployment of renewable sources for electricity generation and theinvestment needed. The deployment of renewables is based on an assessment of the potential and costs for eachsource (bioenergy, hydropower, photovoltaics, concentrating solar power, geothermal electricity, wind, and marine) in
each of the 25 WEM regions. Our modeling, in all scenarios, incorporates a process of learning-by-doing that affects thecosts. By including financial incentives for the use of renewables and nonfinancial barriers in each market, technicaland social constraints as well as the value each technology brings to system in terms of energy, capacity, and flexibility,
the model calculates deployment as well as the resulting investment needs on a yearly basis for each renewable sourcein each region.

METHODOLOGY FOR ENERGY EFFICIENCY PROJECTIONSThe key energy efficiency indicator refers to GDP and total final energy demand.
Economic growth assumptions for the short to medium term are based largely on those prepared by the OECD, theInternational Monetary Fund, and the World Bank. Over the long term, growth in each WEM region is assumed toconverge to an annual long-term rate. This is dependent on demographic and productivity trends, macroeconomic
conditions, and the pace of technological change.
Total final energy demand is the sum of energy consumption for each end use in each final demand sector. In eachsubsector or end use, at least six types of energy are shown: coal, oil, gas, electricity, heat, and renewables. The main oil
products—liquefied petroleum gas (LPG), naphtha, gasoline, kerosene, diesel, heavy fuel oil, and ethane—are modeled
separately for each final demand sector.
In most of the equations, energy demand is a function of activity variables, which again are driven by:Socioeconomic variables: In all end-use sectors GDP and population are important drivers of sectoral activity
variables that determine energy demand for each end use within each sector.

End-user prices: Historical time-series data for coal, oil, gas, electricity, heat, and biomass prices within eachsector are compiled based on IEA’s Energy Prices and Taxes database and several external sources. End-user
prices are then used as an explanatory variable influencing the demand for energy services.

Technological parameters: e.g., recycling in industry, or material efficiency.

All 25 WEM regions for energy demand are modeled in considerable sectoral and end-use detail. Specifically:Industry is separated into six subsectors (with the chemicals sector disaggregated into six subcategories).

Building energy demand is separated into residential and services buildings, which are then separated into six end
uses. Within the residential sector, appliances energy demand is separated into four appliance types.

Transport demand is separated into nine modes, with considerable detail for road transport.

IRENA METHODOLOGY
43
For more details on the Open Source Spatial Electrification Tool, see www.onsset.org; for the latest OnSSET methodology update refer to Korkovelos and others (2018).

CHAPTER 5 • Outlook for SDG 7

141

IRENA scenarios
IRENA’s energy transformation scenarios outlined in this report were developed by the Renewable Energy Roadmaps(REmap) team at IRENA’s Innovation and Technology Centre in Bonn. Since 2014, IRENA’s REmap team44 has produced
a succession of roadmaps with ambitious, yet technically and economically feasible, pathways for deploying lowcarbon technologies to create a clean, sustainable energy future at global, regional, and country levels.
The findings presented in this report are based on IRENA’s 2020 flagship publication Global Renewables Outlook:
Energy Transformation 2050. This report considers policy targets and developments through April 2019; any policychanges and targets announced since then are not considered in the present analysis.
The “Planned Energy Scenario” is the primary reference case for IRENA’s energy transformation study, providing
a perspective on energy system developments based on governments’ current energy plans and other plannedtargets and policies (as of April 2019), including Nationally Determined Contributions under the Paris Agreement
unless the country has more recent climate and energy targets or plans.

The “Transforming Energy Scenario” is IRENA’s energy transformation pathway that describes an ambitious,
yet realistic, energy transformation based largely on renewable energy sources and steadily improved energy
efficiency (though not limited exclusively to these technologies). This pathway would set the energy system on
the path needed to keep the rise in global temperatures to well below 2°C and toward 1.5°C during this century.

Methodology for SDG indicator 7.A.1
This year’s edition of Tracking SDG 7: The Energy Progress Report covers SDG indicator 7.A.1 for the first time.
International financial flows to developing countries in support of clean and renewable energy comprise three
categories of investment flows. Official development assistance (ODA) and other official flows (OOF) to developing
countries together make up the public financial support that donors provide to developing countries for renewableenergy. The additional flows (from the IRENA database) capture the flows to non-ODA recipients in developing regions
and flows from countries and other public institutions not currently reporting to the OECD’s Development AssistanceCommittee (DAC).
SDG indicator 7.A.1 is an indicator jointly produced by OECD and IRENA. The flows covered by the OECD are definedas the sum of official loans, grants, and equity investments that countries on DAC’s list of ODA recipients receivefrom foreign governments and multilateral agencies for the purpose of clean energy research and development andrenewable energy production (including in hybrid systems). These figures are extracted from the OECD/DAC Creditor
Reporting System.
The flows covered by IRENA are defined as all additional loans, grants, and equity investments that developing countries(defined as countries in developing regions, as listed in the United Nations’ M49 composition of regions) receive fromall foreign governments, multilateral agencies, and other development finance institutions for the purpose of clean
energy research and development and renewable energy production (including in hybrid systems). These additionalflows cover the same technologies and other activities (research and development, technical assistance, etc.) as listed
above and, to avoid duplication of data, exclude all flows extracted from the OECD/DAC Creditor Reporting System.

44

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https://www.irena.org/remap.

Tracking SDG 7: The Energy Progress Report 2020

REFERENCES
Frankfurt School–UNEP (United Nations Environment Programme) Centre/BNEF (Bloomberg New Energy Finance).
2019. “Global Trends in Renewable Energy Investment 2019.” Frankfurt School of Finance and Management,Frankfurt am Main, Germany. wedocs.unep.org/bitstream/handle/20.500.11822/29752/GTR2019.pdf?seq
uence=1&isAllowed=y.
IEA (International Energy Agency) (2018), World Energy Outlook 2018, https://www.iea.org/reports/world-energyoutlook-2018.
IEA (2019a), World Energy Outlook 2019, https://www.iea.org/reports/world-energy-outlook-2019.
IEA (2019b), Africa Energy Outlook 2019, https://www.iea.org/reports/africa-energy-outlook-2019.
IEA (2019c), Renewables 2019, https://www.iea.org/reports/renewables-2019.
IEA (2019d), Energy Efficiency 2019, https://www.iea.org/reports/energy-efficiency-2019.
IEA (2019e), World Energy Model Documentation—2019 Version, Paris: IEA.
IEA (2020), Global Energy Review 2019: The latest trends in energy and emissions in 2019, https://www.iea.org/reports/
global-energy-review-2019.
IRENA. 2019. Transforming the Energy System—and Holding the Line on Rising Global Temperatures. Abu Dhabi: IRENA.
IRENA. 2020a. “Renewable Energy Finance: Institutional Capital.” Renewable Energy Finance Brief 02 (January), Abu
Dhabi.
IRENA. 2020b. “Renewable Energy Finance: Green Bonds.” Renewable Energy Finance Brief 03 (January), Abu Dhabi.
IRENA. 2020c. “Renewable Energy Finance: Sovereign Guarantees.” Renewable Energy Finance Brief 01 (January), Abu
Dhabi.
IRENA. 2020d. Global Renewables Outlook: Energy Transformation 2050. Abu Dhabi: IRENA.
IRENA and CPI (Climate Policy Initiative). Forthcoming. Global Landscape of Renewable Energy Finance 2020. Abu
Dhabi: IRENA.
Korkovelos, A., D. Mentis, S. H. Siyal, C. Arderne, H. Rogner, M. Bazilian, M. Howells, H. Beck, and A. D. Roo. 2018. A
Geospatial Assessment of Small-Scale Hydropower Potential in Sub-Saharan Africa. Energies 11 (11): 3100.
https://www.mdpi.com/1996-1073/11/11/3100.
SEforAll (Sustainable Energy for All) and CPI (Climate Policy Initiative). 2019. Energizing Finance: Understanding theLandscape. Vienna and Washington, DC: Sustainable Energy for All.

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CHAPTER 6: TRACKING
SDG 7 PROGRESS ACROSSTARGETS: INDICATORS ANDDATATRACKING SDG 7
PROGRESSACROSS TARGETS:
INDICATORS AND
DATAPhoto: Vincent Tremeau/World BankCHAPTER 6

C

omprehensive and accurate data are a prerequisite for making evidence-based decisions, monitoring trends,
and tracking progress toward policy goals. In developed and developing countries alike, well-designed andappropriately resourced statistical systems play a fundamental role in monitoring progress toward Sustainable
Development Goal 7 (SDG 7).
Leveraging national data efforts worldwide, the global tracking presented in this report is a joint effort of the custodian
agencies responsible for monitoring progress toward the SDG 7 targets—the International Energy Agency (IEA), theInternational Renewable Energy Agency (IRENA), the United Nations Statistics Division (UNSD), the World Bank,and the World Health Organization (WHO).45 International organizations typically collect information from acrosscountries, adding value by promoting coherent standards, definitions, and methodologies for both raw data andderived indicators. The ultimate goal is to produce internationally comparable datasets.46
The quality of global tracking certainly benefits from continuous improvements in national data systems, as countries(i) establish frameworks and institutional arrangements to collect comprehensive data on energy supply and demandand prepare full energy balances; (ii) prepare and carry out surveys of households, businesses, and other categories of
end users; and (iii) apply sound quality-assurance frameworks.47
The data tables that follow this introduction cover all of the indicators of progress toward the SDG 7 targets, assummarized in table 6.1. What follows is a brief description of work done at the national and international levels to
obtain the underlying data. Short descriptions of the methodologies and indicators used in the report were presented
in the final sections of chapters 1–5.

TABLE 6.1 • Targets and indicators for SDG 7
TARGET
7.1 • By 2030, ensure universal access to affordable, reliable, andmodern energy services

INDICATOR
7.1.1 • Proportion of population with access toelectricity
7.1.2 • Proportion of population with primary relianceon clean fuels and technology for cooking

7.2 • By 2030, increase substantially the share of renewable energy inthe global energy mix

7.2.1 • Renewable energy share in total final energy
consumption

7.3 • By 2030, double the global rate of improvement in energy
efficiency

7.3.1 • Energy intensity measured as a ratio of primaryenergy supply to gross domestic product7.A • By 2030, enhance international cooperation to facilitate accessto clean energy research and technology, including renewable energy,
energy efficiency, and advanced and cleaner fossil fuel technology,
and promote investment in energy infrastructure and clean energy
technology

7.A.1 • International financial flows to developing
countries in support of clean energy research anddevelopment and renewable energy production,
including in hybrid systems

45
The World Bank and WHO are responsible for tracking progress toward SDG target 7.1 (access to electricity and clean cooking fuels and technology); IEA, IRENA, and UNSD are responsible for SDG target 7.2 (renewable energy); and IEA and UNSD are responsible for SDG target 7.3 (energy
efficiency). Target 7.A on international cooperation is tracked by IRENA and the Organisation for Economic Co‑operation and Development (OECD).
46
A consultation on harmonized definitions and concepts for energy statistics, conducted across organizations, fed the country-led drafting of theInternational Recommendations for Energy Statistics (IRES), which were adopted by the United Nations in 2011 (https://unstats.un.org/unsd/energystats/methodology/ires/). IRES provides the fundamental definitions behind energy statistics, pointing to international classifications of products(SIEC) and sectors (ISIC). Examples of international data compilations used for this report include IEA’s World Energy Balances (https://www.iea.org/
reports/world-energy-balances-2019) and UNSD’s energy statistics (https://unstats.un.org/unsd/energystats/).
47
Institutional arrangements optimize data production, exchange, and governance across organizations, chiefly statistical offices and specialized
governmental agencies responsible for implementing energy polices (energy ministries). Energy balances are comprehensive accounts of all the energy
entering, exiting, and used in a given country or territory, typically covering production, import, and export of primary energy sources; transformation
into fuels for final consumption; and final consumption within each major end-use sector. Examples of energy balances are available at: https://www.iea.
org/data-and-statistics/data-tables?country=WORLD. Important aspects of data quality are relevance, accuracy, and reliability; timeliness and punctuality; coherence and comparability; and accessibility and clarity. Information on quality assurance frameworks is contained in IRES (https://unstats.
un.org/unsd/energystats/methodology/ires/).

145

ACCESS TO ELECTRICITY
Tracking electrification efforts has been a complex process that has raised many challenges, the first being to devise auniversally applicable and transparent approach. Measuring access to electricity requires tracking cumulative progress
across interventions by a variety of players—governments, energy utilities, private sector companies, funding agencies,and development organizations at the national and international levels. Particularly challenging are the socioeconomic
complexities of low-access countries. Measuring access also implicates a variety of technologies—not only national
grids but mini grids and off-grid solutions, such as solar home systems. Finally, it requires assessing the number ofpeople who actually benefit from these interventions, as well as the nature and degree of improvement they provide.
But however difficult it may be, measuring access is critical to enable governments and practitioners to understandthe current status of access, to identify bottlenecks to further electrification, and to achieve universal access goals in
more efficient ways.
The definition and measurement of access to electricity should focus not only on the number of users benefittingfrom improved energy access, but also on the nature and degree of improvement across various attributes: capacity(adequacy), availability, reliability, affordability, quality, legality, health impact, safety, and convenience, among others.
To provide this fuller picture, and to help prioritize investment and track progress, a set of international agencies joined
together to produce a multi-tier framework (MTF) for household surveys.48 The MTF has been rolled out by national
statistical offices and the World Bank in about 16 countries since 2016. Given the paucity of data for multi-tier metrics,
however, standardized country-level surveys and supply-side data from governments and utilities must still be used tocomplement the MTF approach.
Additional methods of improving the tracking of access to electricity are: (i) developing the capacity of national
statistical offices to collect energy data (for example, through workshops organized by development partners on datacollection and analysis for the energy sector); (ii) helping governments apply new technology and data analytics,
since survey design can be challenging if the national census is outdated or if a census has never been conducted;(iii) improving and adapting the usability of existing datasets for energy practitioners; (iv) exploring the use of largescale open databases, such as satellite data. Most microdata (including household surveys, enterprise surveys,
and agricultural surveys) contain information useful for energy practitioners and the ministries of energy. However,significant time and effort are usually required to extract from such sources data related to energy access, including
socioeconomic status, electrification status, and village-level information. Data harmonization and standardization
could help more end users access and use such datasets for project design and policy formulation.

ACCESS TO CLEAN COOKING SOLUTIONS
To monitor SDG 7 on access to clean cooking and SDG 3 on health, country and regional estimates are derived using
a nonparametric statistical model. “Clean cooking” is defined as the performance of a particular fuel and technology
combination, as measured by its emissions. Currently, the analysis for SDG indicator 7.1.2 relies only on cooking fuelas a practical proxy for the population practicing clean cooking. This is due to a lack of globally representative data on
the cooking technologies used by households. Therefore, households considered to have access to clean cooking—for
purposes of tracking SDG indicator 7.1.2—are those that rely primarily on electricity, biogas, solar, alcohol fuels, naturalgas, and liquefied petroleum gas for cooking.
In future, designing, implementing and monitoring the effectiveness and impacts of policies and programs for clean
cooking will depend on better survey coverage of all the types of cooking fuels and technologies used, as well as theirduration of use. Presently, country-level estimates of clean cooking access are also used to estimate the incidenceof disease caused by household air pollution and ultimately to the “mortality rate from the joint effects of ambientand household air pollution,” which is one of the SDG indicators of environmental health (SDG indicator 3.9.1). By
enhancing data collection on the parallel use of multiple cooking solutions in the home (a practice known as “stove
stacking,” common in low- and middle-income countries), more refined estimates of human exposure to pollution andthe related disease burden will become possible.
Simple changes to surveys can greatly improve the monitoring of trends and effects related to clean cooking. The clean

48
The agencies contributing to the development of the MTF were the Energizing Development Program (EnDev), the Energy Sector Management
Assistance Programme, the Global Alliance for Clean Cookstoves, IEA, Practical Action Consulting, the United Nations Development Programme, the UN
Foundation, the UN Industrial Development Organization, the World Bank, and WHO.

146

Tracking SDG 7: The Energy Progress Report 2020

cooking estimates presented in this report, for example, drew on more robust data on the specific fuels households
use for cooking, which in turn made possible the application of more advanced modeling techniques. The result is theestimation, presented here for the first time, of the percentage of households in each country and region primarily
using biomass, charcoal, coal, kerosene, gaseous fuels, and electricity. Armed with such specific fuel-use estimates,
decision-makers can better monitor trends and the effects of changes in subsidies, tariffs, and other policies.
As refinements in household surveys and censuses are made, countries should seize the opportunity to gather amore complete picture of household energy use, including fuels and technologies employed for heating and lighting,which can also have a significant effect on air pollution within the household. Steps have already been taken to enable
stakeholders to better monitor household energy use and its effects through the use of a set of harmonized questions
for national household surveys and censuses. More information on such initiatives by WHO and the World Bank can befound in chapter 2.

RENEWABLE ENERGYProgress on renewable energy is tracked as the share of renewables in total final energy consumption,49 which depends
on the availability of comprehensive data across all energy sources, renewable and non renewable alike, and across thesectors of supply, transformation, and final consumption. In terms of data, computation of this indicator relies on theavailability of a full energy balance, as well as some assumptions regarding electricity and heat.
Two specific challenges in tracking the penetration of renewables are the need to better monitor the rapid expansionof geographically distributed resources (solar photovoltaic, wind, and other resources powering mini-, micro-, and offgrid systems) and to enhance countries’ capacity to measure traditional household uses of biomass (solid biofuels),
which remains the largest segment of renewable energy in the developing world.
Arriving at better estimates of the latter will require dedicated efforts—either enhancing existing surveys with an energy
module or establishing new energy surveys. Survey-based results are very valuable; often they trigger significant
revisions of previous estimates—and might well do so in the case of tracking progress toward SDG target 7.2.
A broader question about biomass is the extent to which its use should be considered sustainable. Although forests aretechnically “renewable,” traditional harvesting practices often cause deforestation.

ENERGY EFFICIENCYFor purposes of SDG 7, energy efficiency is tracked as energy intensity, the ratio of total energy supply to economic
output. Determining the total energy supply requires robust information on production of and trade in all types ofenergy. The supply information may be collected from administrative sources or by surveying the key energy suppliers.
Reasonably good information on supplies of most energy sources is available in most countries, with the notable
exception of supplies of solid biofuels in several countries. Thus, where solid biofuels are a significant part of the overall
energy mix, estimates of total energy supply may be less certain.
To assess progress in energy efficiency, overall energy intensity should be complemented by analysis of energy demand
drivers across the principal end-use sectors, such as industry, transport, and buildings. Given the diversity of end uses,
demand-side data collection is inherently more complex, time consuming, and costly than on the supply side. Direct
consumer surveys may be necessary, especially when energy suppliers cannot provide detailed data on how muchenergy is being delivered to the various types of energy users.
To analyze sectoral progress in energy efficiency, countries are encouraged to monitor intensities at the end-use level,at least for priority sectors. Examples of energy efficiency indicators include, for transport, energy per passengerkilometer (or tonne-kilometer for freight), by vehicle type; for buildings, energy for space heating and cooling as afunction of area; and for industry, energy by quantity of physical production of a given good. IEA’s 2014 statistics
report, “Energy Efficiency Indicators: Fundamentals on Statistics” (https://www.iea.org/reports/energy-efficiencyindicators-fundamentals-on-statistics), includes a methodological framework for energy efficiency indicators, as wellas country experiences.

49

The methodology used to derive total final energy consumption is part of IRES (https://unstats.un.org/unsd/energystats/methodology/ires/).

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data147

Developing such indicators requires not only finer disaggregation of data but also greater coordination across entities
responsible for matters beyond the energy sector, such as building registers, vehicle registrations, and so on. Despite
the challenges, many countries have started to collect end-use data and compile energy efficiency indicators to bettersupport their policy and planning.50

INTERNATIONAL FINANCIAL FLOWS TO DEVELOPING COUNTRIES IN SUPPORTOF CLEAN AND RENEWABLE ENERGY
Data on flows of development finance are susceptible to changes and adjustments that call for careful attention todetail, standardization of cycles of data collection and management, and continuous revision of commitment values.
Based on the nature of SDG indicator 7.A.1, four areas of improvement in the tracking of international investment
flows are suggested: (i) improving investment tracking; (ii) standardizing commitment details; (iii) centralizing datacollection efforts; and (iv) presenting constant flows.
Improving investment tracking. It is important to know how aid recipients spend the funds they receive. The practices
presently in use are not sufficient to track public aid from origin to end. Such tracking requires a system of identification
numbers to trace commitments from public investors through to their end uses in organizations and projects. Recipients
may include financial instruments (such as energy bonds and funds), multilateral organizations, or projects involving
one or more energy technologies. Donors often have trouble specifying how their commitments should be spread
across various energy technologies. International flows may go through additional stages of investment after the initialcommitment, passing through local governments, ventures, or funds. Successive revisions of historic investment flows
may include several years’ of investments, since individual commitments may be announced (and counted) before
they materialize. Some of these commitments may be cancelled or changed, altering the values of existing data.
Standardizing commitment details. To increase the accuracy of tracking SDG indicator 7.A.1 it would be desirable tostandardize commitment details by sharing best practices among public investors, refining reporting directives, andencouraging public investors to provide energy details that meet international standards. Data collection related toinvestments tends to follow the norms and practices of the financial world and often is short on energy-related details.
Thus, committed flows are often linked to projects that involve multiple renewable energy technologies or that mix
energy efficiency and other end uses, compromising their comparability with other data being considered. Information
may be lost owing to nonstandard reporting of public flows across investors. For these reasons, only a limited amountof commitment information may match across investors.
Centralizing data collection. Data collection can be centralized by encouraging preformatted questionnaires andonline data entry to increase comparability across public investors. The OECD’s Creditor Reporting System databaseis exemplary in this regard. However, collection of most data on international public investments in clean energy andrenewables remains decentralized, reducing the consistency of commitment data.
Presenting constant flows. International commitments must be corrected for currency exchange rates and inflation if
they are to be comparable across countries and over time. SDG indicator 7.A.1 uses the OECD methodology to deflate
international flows by first adjusting for inflation from the year the flows occurred to a baseline year (2017), and thenconverting local currency values to U.S. dollars using the exchange rates in the baseline year (2017).

50
Examples include IEA’s energy efficiency indicators: https://www.iea.org/reports/energy-efficiency-indicators-2019; and the Odyssée databasefor Europe: https://www.indicators.odyssee-mure.eu/energy-efficiency-database.html.

148

Tracking SDG 7: The Energy Progress Report 2020

CONCLUSIONT

he work performed for this report has highlighted the need for good quality data to inform policy at the national,
regional, and international levels, as well as opportunities to further develop national statistical capacity and toenhance data quality through national and international cooperation.

At the national level, cooperation between national statistical offices and institutions in various policy domains will be
key to optimizing the use of data-collection resources. For example, household surveys could and should be designed
to support tracking of several SDG 7 targets at once, such as clean cooking and energy efficiency, as well as of targets
beyond SDG 7, such as those on quality of life, air pollution, and health.51
International cooperation strengthens the world’s ability to track SDG 7 by raising awareness of the importance of goodquality data to inform policy; by proposing standardized methodologies for indicators as well as common frameworks
for data-collection surveys; by compiling international databases; and by supporting the development of statistical
capacity in countries and regions. Tracking SDG 7 has given the custodian agencies an opportunity to further improvetheir collaboration on data, both with countries and between one another.
The custodian agencies would like to acknowledge the work and dedication of all their colleagues working to collectenergy data across national administrations worldwide. It is they who make possible the international tracking work
reflected in this report.

51
For example, clean cooking and space heating are significantly linked for rural households in colder climates. More broadly, all end uses of energy
within a household (lighting, appliances, cooking, heating, cooling) can be addressed in a single survey.

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

149

150

Tracking SDG 7: The Energy Progress Report 2020

100
100
100
96
100
100

Aruba

Australia

Austria

Azerbaijan

BahamasBahrain

100
68
10
100

BelarusBelgium

BelizeBenin

Bermuda6
87

Botswana

Brazil

h

94

27

100

100

Bosnia and Herzegovina
m

31
70

57

Bolivia (Plurinational
State of)

100

21

79

100

Bhutanmm

100

Barbados
100

32
100

100

100

99

100

100

92

99

96

97

95

23

100

7

m

m

m

m

m

m

100

Bangladesh

92

96

Antigua and Barbuda
98

90

Anguilla

Armenia

12

AngolaArgentina

100

AndorraAmerican Samoa

m

h

g

m

e

m

m

m

d

m

c

m

m

e

d

m

99

53

100

88

73

100

34

90

100

100

100

55

100

100

100

100

100

93

100

99

98

98

33

100

99

Algeria

m

100

98

100

96

m

100

Albania

2000

Afghanistan

1990

2010

m

c

m

g

e

m

m

m

g

m

m

m

m

e

d

e

m

m

d

100

58

100

92

95

100

38

92

100

100

100

73

100

100

100

100

100

100

100

100

100

100

42

100

100

100

72

2015

Total electricity access rate (%)

43

Country

Data provided by the World BankSDG 7.1.1 - ACCESS TO ELECTRICITY

DATA

h

g

h

m

c

m

m

m

m

m

m

m

m

d

m

d

m

m

d

100

65

100

96

100

100

42

100

100

100

100

85

100

100

100

100

100

100

100

100

100

100

43

100

100

100

99

2018

m

m

m

m

m

m

m

m

m

m

m

m

m

m

100

81

100

100

100

100

67

98

100

100

100

97

100

100

100

100

100

100

100

100

100

74

100

100

100

100

2018

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Urban
electricity
access rate (%)

100

28

100

86

100

100

18

100

100

100

100

78

100

100

100

100

100

100

100

100

100

100

100

100

98

2018

m

m

m

m

m

m

m

m

m

m

m

m

m

m

Rural electricity
access rate(%) b

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

151

2000

100

CanadaCayman Islands

100
100
100

Curaçao

CyprusCzechia
m

m

93

Cuba

100

100

100

97

100

48

m

m

k

100

Croatiam

38

Côte d’Ivoire

99

98

Costa Rica

100

100

100

98

100

58

99

99

97

97

95

m

d

100

Cook Islands

95

m

100

100

Congo

Comoros

d

100

m

70

16

Colombia

m

97
100

42

90

China, Macao Special
Administrative Region

m

99

6

10

100

100

21

100

China, Hong Kong Special
Administrative Region

h

c

m

m

31
53

40

94
100

China

92

Chile
98

3

Channel Islands

6

Chad

100

Central African Republic

h100

Cameroon
100

17
41

30

Cambodiac

Cabo Verde
81

57

Burundi
37

5

100

100

13

d

m

m

99

3

100

100

95

9

m

Bulgaria
4

m

100

Burkina Fasom

100

Brunei Darussalam

1990
92

British Virgin Islands

Country
2010

m

m

m

m

h

h

m

m

k

c

c

m

m

d

e

d

d

m

m

100

100

100

99

100

63

99

100

60

74

98

100

100

100

100

8

24

100

100

59

69

87

9

16

100

100

100

2015

Total electricity access rate (%)

m

m

m

m

g

h

c

h

m

m

h

d

m

m

m

m

m

100

100

100

100

100

67

100

100

69

82

100

100

100

100

100

12

32

100

100

63

92

94

11

14

100

100

100

2018

m

m

m

m

m

m

m

m

m

d

m

m

m

100

100

100

100

100

100

100

100

92

94

100

100

100

100

100

42

55

100

100

93

100

92

62

62

100

100

100

2018

m

m

m

m

m

m

m

m

m

d

m

m

m

Urban
electricity
access rate (%)

100

100

100

100

100

33

100

20

77

100

100

100

100

100

3

16

100

100

23

89

97

3

3

100

100

100

2018

m

m

m

m

m

m

m

m

m

d

m

m

m

Rural electricity
access rate
(%) b

152

Tracking SDG 7: The Energy Progress Report 2020

m

66
12

French Polynesia

Gabon

Gambia

24
100
100
100
82

Ghana

Gibraltar

GreeceGreenland

Grenada

97

100

France100

100Germanym

100

Finland

Georgia

m

63

Fiji

m

m

m

m

m

100

100

Faroe Islands

86

100

100

100

44

100

99

34

74

100

100

100

76

13
m

29
100
20

m

85
65

Ethiopia

Estonia

94
98

Eswatini

18100

Eritrea

Egypt
73

95

Ecuador64

90

Dominican Republic

Equatorial Guinea

80

Dominica

El Salvador

81

67
89

56

56

Djibouti

100

100

7

Democratic Republic of the
Congo

2000

Denmark

7

1990

Democratic People’s
Republic of Korea

Country

m

m

m

e

m

c

d

m

m

m

m

d

m

h

d

h

m

c

90

100

100

100

64

100

99

47

92

100

100

100

89

100

33

46

100

40

66

92

99

97

98

94

56

100

13

29

2010

m

m

m

e

m

m

m

m

m

c

m

h

h

h

m

92

100

100

100

76

100

100

54

90

100

100

100

95

100

29

66

100

46

66

95

99

99

99

100

58

100

16

41

2015

Total electricity access rate (%)

m

m

m

m

m

m

m

m

d

m

h

g

h

h

m

95

100

100

100

82

100

100

60

93

100

100

100

100

100

45

77

100

50

67

100

100

100

100

100

60

100

19

49

2018

m

m

m

m

c

m

m

m

m

m

m

2018

100

100

100

94

100

100

76

97

100

100

100

100

100

92

97

100

77

90

99

100

100

100

100

71

100

51

56

m

m

m

m

c

m

m

m

m

m

m

Urban
electricity
access rate (%)

100

100

100

100

67

100

100

35

63

100

100

100

99

100

33

70

100

35

7

100

100

100

100

100

24

100

40

2018

m

m

m

m

m

m

m

m

m

m

Rural electricity
access rate(%) b

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

153

m

m
h
m
d

100
100
70
100
97
98

Isle of Man

IsraelItaly

JamaicaJapan

JordanKazakhstan

100
100
15
100
98

KuwaitKyrgyzstan

Lao People’s Democratic
Republic

LatviaLebanon

m

99

100

43

100

100

100

100

Kosovo
m

15
51

26

Kiribati

99

99

100

84

100

100

100

100

97

98

86

59

100

100

67

34

Kenya
m

m

m

100

Ireland
m

95
100

Iraq

63
96

42

India

Iran (Islamic Republic of)100

IcelandIndonesia

55
100

Haiti

Hungary

26

GuyanaHonduras

68m

Guinea75

163

Guinea-Bissau

73

60

2000
100

Guatemala

1990
100

Guam

Country

m

m

m

m

m

m

m

m

d

g

m

m

d

h

m

100

100

71

99

100

99

63

19

100

99

100

92

100

100

100

100

98

99

94

76

100

100

81

37

82

6

27

84

100

2010

m

i

m

e

d

m

g

m

m

m

m

g

g

m

m

h

g

m

100

100

90

100

100

100

91

42

100

100

100

95

100

100

100

100

99

100

98

88

100

100

90

41

88

20

34

91

100

2015

Total electricity access rate (%)

m

e

m

m

e

d

c

m

g

m

m

m

m

g

d

m

m

h

m

100

100

98

100

100

100

100

75

100

100

100

99

100

100

100

100

100

100

99

95

100

100

92

45

92

29

44

95

100

2018

m

c

m

m

k

l

g

m

m

m

m

m

c

g

m

m

d

m

100

100

99

100

100

100

94

84

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

79

97

53

87

96

100

2018

m

c

m

m

k

m

m

m

m

m

c

g

m

m

d

m

Urban
electricity
access rate (%)

100

100

97

100

100

100

72

100

99

100

98

100

100

100

100

100

100

97

93

100

100

81

4

90

10

20

94

100

2018

m

c

m

m

k

m

m

m

m

m

c

g

m

m

m

Rural electricity
access rate
(%) b

154

Tracking SDG 7: The Energy Progress Report 2020

m

100
100
9

Liechtenstein

Lithuania

Luxembourg

Madagascar

2000

97

94
77

Malaysia

Maldives

25
100

Namibia

Nauru

100
100

New Caledonia

New Zealand
m

100

100

Netherlands

100

100

28

Nepal

100

37

42

30

Myanmar

70

100

6

m

m

67

100

46

98

99

19

Mozambique

49

MonacoMorocco100

Micronesia (Federated
States of)

100

28

MexicoMontenegro

95

Mauritius

Mongolia

100

Mauritaniam5

Marshall Islands

60

53

Malta
69

9
100

100

Mali

84

5

14

100

100

100

100

4

Malawi

m

m

m

100

Libya

1990

100

Liberia

LesothoCountry

m

m

m

d

m

e

m

e

h

e

k

m

e

d

k

m

m

m

k

c

100

100

100

69

99

44

49

18

92

100

79

100

65

99

100

34

89

100

28

99

99

9

18

100

100

100

81

5

17

2010

m

m

m

g

g

m

c

m

e

d

m

d

m

m

m

100

100

100

85

99

52

61

24

100

100

88

100

76

99

97

40

93

100

38

100

100

11

20

100

100

100

73

16

32

2015

Total electricity access rate (%)

m

m

m

g

g

d

m

m

d

c

m

d

d

m

m

m

g

100

100

100

94

100

54

66

31

100

100

98

100

82

100

97

45

96

100

51

100

100

18

26

100

100

100

67

26

47

2018

m

m

m

l

d

c

c

m

m

d

g

m

m

m

k

c

2018

100

100

100

96

100

72

92

72

100

100

100

100

94

100

88

82

96

100

86

100

100

55

70

100

100

100

100

44

71

m

m

m

l

d

c

c

m

m

d

m

m

m

c

Urban
electricity
access rate (%)

100

100

100

93

36

55

8

100

100

95

100

79

100

100

1

98

100

25

100

100

10

100

100

100

7

38

2018

m

m

m

c

m

m

m

m

m

Rural electricity
access rate(%) b

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

155

100
100
70
97
70

Northern Mariana Islands

NorwayOman

Pakistan

Palau

Panama

79

Samoa

88

80

68

89

66

100

100

Saint Vincent and the
Grenadines

m

m

47

Russian Federation

100

84

100

Romaniam

Saint Martin (French Part)

100

Republic of Moldova

100

100

Saint Lucia

100

Republic of Korea

m

6

100

Qatar

100

100

95

100

Puerto Rico

m

75
100

91

100

PortugalmSaint Kitts and Nevis

100

Poland72

Rwanda64
100Philippines

Peru

89

81
61

Paraguay

9

81

98

70

100

100

Papua New Guinea

e

m

100

North Macedonia
100

96
100

m

93
100

Nigeria

Niue

6
43

2
d

2000
73

27

1990

Niger

66

NicaraguaCountry

e

d

d

m

m

m

m

m

m

h

e

m

m

m

c

k

97

93

64

94

100

10

100

100

100

100

100

100

100

100

85

88

97

20

87

98

70

100

100

100

100

99

48

13

79

2010

e

d

m

m

m

m

m

m

m

m

h

h

g

e

m

m

m

m

d

100

100

100

97

100

23

96

100

100

100

100

100

100

100

89

94

99

44

95

99

71

100

100

100

100

100

53

17

84

2015

Total electricity access rate (%)

g

m

d

m

m

m

m

m

m

m

m

f

h

h

m

m

m

m

d

100

100

100

100

100

35

100

100

100

100

100

100

100

100

95

95

100

59

100

100

71

100

100

100

100

100

57

18

88

2018
l

m

m

m

m

m

m

m

m

m

m

g

m

m

m

m

m

m

d

100

98

100

98

100

89

100

100

100

100

100

100

100

100

98

99

100

82

100

100

100

100

100

100

100

100

82

48

100

2018

m

m

m

m

m

m

m

m

m

m

g

m

m

m

m

m

m

d

l

Urban
electricity
access rate (%)

100

100

100

100

100

23

100

100

100

100

100

100

100

100

93

82

100

55

100

100

54

100

100

100

100

31

12

71

2018

m

m

m

m

m

m

m

m

m

m

g

m

m

m

m

m

m

Rural electricity
access rate
(%) b

156

Tracking SDG 7: The Energy Progress Report 2020

2000

91

85

78
93

82

98

Trinidad and Tobago

Thailand

Tonga

Tajikistan

93

17

98
80

Syrian Arab Republic

18

96

Switzerland
100

100

Togo

m

100

Sweden23
96

Timor-Lestem

100

Surinamed3396State of Palestine

Sudan

69
100

53

100

98

m

Sri Lanka

100

Spain

South Sudan

5

100

72

61

m

100
100

South Africa

100

Sloveniam

Somalia

100

Slovakia

100

5

100

Sint Maarten (Dutch part)

m

m

e

c

d

c

m

m

c

g

m

m

m

100

92

31

38

100

98

93

100

100

91

41

100

85

100

2

83

21

34

100

100

100

100

11

Solomon Islands

100

Singapore

Sierra Leone

97

Seychelles

100

57

100

60

100

8

90

Serbia
m

c

c

m

94

38
100

100

53

100

21
m

m

100

Saudi Arabia

1990

Senegal41
100

Sao Tome and Principe

100

San Marino

Country
2010

m

c

d

f

g

m

m

c

g

g

m

e

g

m

m

m

m

c

e

m

g

m

m

100

96

45

67

100

98

90

100

100

95

49

100

94

100

18

86

30

55

100

100

100

100

20

100

100

61

100

66

100

2015

Total electricity access rate (%)

m

e

c

g

m

m

g

m

g

d

m

m

m

m

m

k

d

m

m

100

99

51

86

100

99

86

100

100

97

60

100

100

100

28

91

35

67

100

100

100

100

26

100

100

67

100

71

100

2018

m

d

k

m

m

c

m

m

m

m

m

g

m

m

m

l

m

100

99

92

100

100

99

100

100

100

99

84

100

100

100

47

92

60

77

100

100

100

100

53

100

100

92

100

77

100

2018

m

d

m

m

c

m

m

m

m

m

g

m

m

m

l

m

Urban
electricity
access rate (%)

100

99

22

79

100

99

69

100

100

94

47

100

99

100

24

90

15

64

100

100

100

100

6

100

100

44

100

56

100

2018

m

d

m

m

m

m

m

m

m

m

m

m

m

Rural electricity
access rate(%) b

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

157

91

Turks and Caicos Islands

Tuvalu100
100
2

United Arab Emirates

United Kingdom of GreatBritain and Northern Ireland

United Republic of Tanzania

45

Zimbabwe

Central Asia and Southern
Asia

Zambia

86

14
30

Yemen

Latin America and the
Caribbean

37

72

78

Viet Nam

100

98

Venezuela (Bolivarian
Republic of)Northern America andEurope4

Vanuatu

World

87
50

99

Uzbekistan

e
34

17

99

22

100

98

100

97

Uruguaym

100

United States Virgin Islands

100

100

10

100

United States of America
m

m

100

100

100

Ukrainem

8

94

Ugandam

89

Turkmenistan
96

97
100

93

e

60

92

100

78

2000
95

99

1990

Turkey89

Tunisia

Country

e

h

m

m

m

m

m

e

d

g

40

22

74

98

99

44

100

99

100

100

15

100

100

100

12

97

100

100

100

100

75

96

100

83

2010

e

g

m

m

d

m

m

m

g

m

i

i

j

34

31

71

100

100

52

100

100

100

100

27

100

100

100

19

99

100

100

100

100

86

97

99

87

2015

Total electricity access rate (%)

d

g

h

m

m

m

m

m

d

m

c

g

41

40

62

100

100

62

100

100

100

100

36

100

100

100

43

100

100

100

100

100

92

98

100

90

2018

k

m

m

m

m

m

m

l

m

c

85

77

85

100

100

94

100

100

100

100

68

100

100

100

58

100

100

100

100

100

100

100

100

97

2018

k

m

m

m

m

m

m

l

m

c

Urban
electricity
access rate (%)

20

11

49

100

100

51

100

100

100

100

19

100

100

100

38

100

100

100

100

100

88

93

100

80

2018

m

m

m

m

m

m

m

c

Rural electricity
access rate
(%) b

158

Tracking SDG 7: The Energy Progress Report 2020

85
17
80

Western Asia and Northern
AfricaSub-Saharan Africa

Oceania
80

25

87

91

2000

82

34

92

96

2010

87

39

93

97

2015

91

47

94

98

2018

99

78

99

99

2018

Urban
electricity
access rate (%)

73

27

86

97

2018

Rural electricity
access rate(%) b

Source: World Bank

m. Data from assumption: Countries considered “developed” by the UN are assumed to have an electrification rate of 100%. Countries that are classified as High Income Countries (HIC) are also assumed
to have an electrification rate of 100% from the time the country first became a HIC, unless survey data was collected.

l. Based on Multi-Tier Framework (MTF)

k. Based on other official sources

j. Based on Middle East and North Africa Poverty Database (MNAPOV)

i. Based on Europe and Central Asia Poverty Database (ECAPOV)

h. Based on Socio-Economic Database for Latin America and the Caribbean (SEDLAC)

g. Based on other National Surveys conducted by national statistical agencies

f. Based on Living Standards Measurement Survey (LSMS)

e. Based on Census

d. Based on Demographic and Health Survey (DHS)c. Based on Multi-Indicator Cluster Survey (MICS)

b. Rural data are calculated based on the urban and total population with access and are not based on a statistical model.

a. Most surveys report data on the percentage of households with access to electricity rather than on the percentage of the population with access.

Note: Unless otherwise noted, data are World Bank estimates based on the statistical model described in chapter 1.

86

1990

Eastern Asia and Southeastern Asia

Country

Total electricity access rate (%)

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

159

>95

Algeria

84

Angola95
79

Argentina

Armenia

94

80<5Belize

Benin
28
63
52

BhutanBolivia (Plurinational
State of)Bosnia and Herzegovina

Bermuda>95>95

Belgium

>95

95

81

92

89

<5

>95

>95

Belarus

35

>95

>95

>95

>95

>95

>95

>95

Barbados

8>95

Bahrain

Bangladesh

70>95

Bahamas>95

Austria

Azerbaijan>95

Australia

Aruba

>95

Antigua and Barbuda
>95

>95

44

>95

67

48

>95

Anguilla

Rural clean
cooking
accessrate (%)

Total clean
cooking
accessrate (%)

30

18

10

<5

67

>95

88

>95

<5

>95

>95

44

>95

>95

53

68

>95

8

>95

>95

17

<5

44

77

64

5

83

>95

>95

>95

12

>95

>95

93

>95

>95

>95

>95

>95

47

>95

>95

67

20

69

>95

>95

9

>95

>95

>95

>95

41

>95

>95

>95

>95

>95

>95

>95

>95

81

>95

>95

86

72

2010
Urban
clean
cooking
accessrate (%)

2000
Urban
clean
cooking
accessrate (%)

AndorraAmerican Samoa

11
39

Albania

Total clean
cooking
accessrate (%)

Afghanistan

Country

Data provided by WHO

22

41

47

<5

73

>95

>95

>95

<5

>95

>95

87

>95

>95

92

88

>95

7

>95

>95

46

6

Rural clean
cooking
accessrate (%)

45

82

74

5

83

>95

>95

>95

18

>95

>95

>95

>95

>95

>95

>95

>95

48

>95

>95

76

29

Total clean
cooking
accessrate (%)

2015

65

>95

>95

9

>95

>95

>95

>95

52

>95

>95

>95

>95

>95

>95

>95

>95

77

>95

>95

90

82

Urban
clean
cooking
accessrate (%)

SDG 7.1.2 – ACCESS TO CLEAN FUELS AND TECHNOLOGIES FOR COOKING

19

51

60

<5

74

>95

>95

>95

6

>95

>95

92

>95

>95

95

93

>95

7

>95

>95

58

14

Rural clean
cooking
accessrate (%)

45

84

77

5

83

>95

>95

>95

24

>95

>95

>95

>95

>95

>95

>95

>95

48

>95

>95

80

37

Total clean
cooking
accessrate (%)

2018

64

>95

>95

8

95

>95

>95

>95

60

>95

>95

>95

>95

>95

>95

>95

>95

75

>95

>95

92

86

Urban
clean
cooking
accessrate (%)

19

53

64

<5

74

>95

>95

>95

9

>95

>95

94

>95

>95

95

94

>95

8

>95

>95

62

21

Rural clean
cooking
accessrate (%)

160

Tracking SDG 7: The Energy Progress Report 2020

Brazil

71

63
<5
10
>95

Cabo VerdeCambodia

Cameroon

Canada

<5

Chad

43

China

>95
38
93

18
85

Costa Rica

Côte d’Ivoire

Croatia

Cuba

>95

15

<5

81

9

Congo
89

<5

Comoros

93

69

>95

7

<5

>95

90

Cook Islands

78

Colombia

China, Macao Special
Administrative Region

China, Hong Kong
Special Administrative
Region>95

Chile

Channel Islands<5

Central African Republic

Cayman Islands

15
20

<5

Burundi
<5

<5

12

>95

>95

Burkina Faso

Bulgaria

Brunei Darussalam
>95

45
88

Botswana

British Virgin Islands

Total clean
cooking
accessrate (%)

Country

Rural clean
cooking
accessrate (%)

Total clean
cooking
accessrate (%)

76

<5

78

43

<5

<5

34

24

>95

<5

<5

>95

<5

<5

31

<5

<5

>95

51

20

88

17

92

80

17

<5

85

53

>95

<5

<5

>95

20

12

70

<5

6

>95

94

56

89

36

>95

>95

26

7

>95

77

>95

9

<5

>95

37

46

91

<5

21

>95

>95

78

2010
Urban
clean
cooking
accessrate (%)

2000
Urban
clean
cooking
accessrate (%)

88

<5

80

33

<5

<5

40

27

>95

<5

<5

>95

<5

<5

33

<5

<5

>95

69

29

Rural clean
cooking
accessrate (%)

87

23

94

78

26

6

90

60

>95

<5

<5

>95

23

17

75

<5

8

>95

>95

55

Total clean
cooking
accessrate (%)

2015

86

47

>95

>95

38

14

>95

81

>95

12

<5

>95

42

59

93

<5

28

>95

>95

75

Urban
clean
cooking
accessrate (%)

92

<5

84

26

<5

<5

56

33

>95

<5

<5

>95

<5

7

39

<5

<5

>95

77

26

Rural clean
cooking
accessrate (%)

86

29

95

77

32

8

93

64

>95

<5

<5

>95

24

22

78

<5

10

>95

>95

53

Total clean
cooking
accessrate (%)

2018

85

57

>95

>95

46

17

>95

82

>95

13

<5

>95

43

65

94

<5

32

>95

>95

72

Urban
clean
cooking
accessrate (%)

93

<5

87

23

<5

<5

69

36

>95

<5

<5

>95

<5

10

42

<5

<5

>95

80

24

Rural clean
cooking
accessrate (%)

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

161

Ethiopia>95

FinlandFranceGeorgia

Germany
6

49>95

Gambia

Ghana

65
<5

Gabon

French Polynesia

30
>95

Fiji

14

>95

86

6

80

>95

>95

51

<5

Faroe Islands

60

24
<5

Eswatini

31

81

Estonia

Equatorial Guinea
1119

El Salvador

>95
>95

>95

56

Egypt

<5

84

Ecuador

95

>95

5

>95

11

<5

>95

>95

>95

88

Dominican Republic

Total clean
cooking
accessrate (%)

<5

>95

11

<5

15

>95

>95

12

<5

10

>95

<5

5

24

75

70

67

28

<5

>95

<5

<5

>95

>95

16

>95

65

<5

81

>95

>95

30

<5

39

>95

8

23

77

>95

94

87

82

6

>95

<5

6

>95

>95

29

>95

93

<5

90

>95

>95

47

9

79

>95

21

34

92

>95

>95

95

>95

7

>95

10

9

>95

>95

Urban
clean
cooking
accessrate (%)

Rural clean
cooking
accessrate (%)

Urban
clean
cooking
accessrate (%)

Eritrea

77
84

Dominica

55

Democratic Republic of
the Congo>95<5

Democratic People’s
Republic of Korea

Djibouti>95

Czechia

Denmark>95

Total clean
cooking
accessrate (%)

CyprusCuraçaoCountry

2010

2000

<5

>95

34

<5

29

>95

>95

11

<5

24

>95

<5

5

50

>95

83

69

38

<5

>95

<5

<5

>95

>95

Rural clean
cooking
accessrate (%)

23

>95

75

<5

86

>95

>95

29

<5

48

>95

9

24

86

>95

94

88

82

6

>95

<5

9

>95

>95

Total clean
cooking
accessrate (%)

38

>95

94

<5

93

>95

>95

45

17

86

>95

21

34

94

>95

>95

94

>95

7

>95

9

13

>95

>95

Urban
clean
cooking
accessrate (%)

2015

7

>95

53

<5

38

>95

>95

9

<5

32

>95

<5

5

70

>95

85

69

38

<5

>95

<5

<5

>95

>95

Rural clean
cooking
accessrate (%)

28

>95

81

<5

87

>95

>95

28

5

54

>95

9

24

91

>95

94

89

82

6

>95

<5

10

>95

>95

Total clean
cooking
accessrate (%)

43

>95

94

<5

94

>95

>95

44

24

88

>95

20

33

95

>95

>95

94

>95

8

>95

8

16

>95

>95

Urban
clean
cooking
accessrate (%)

2018

9

>95

63

<5

42

>95

>95

8

<5

39

>95

<5

<5

81

>95

85

70

36

<5

>95

<5

<5

>95

>95

Rural clean
cooking
accessrate (%)

162

Tracking SDG 7: The Energy Progress Report 2020

30
>95
>95
23
6
94
78
>95

Haiti

Honduras

Hungary

Iceland

India

Indonesia

Iran (Islamic Republic
of)

Iraq

Ireland

>95

76
>95
>95
84
<5
<5

JamaicaJapan

JordanKazakhstan

Kenya

Kiribati

Kosovo

>95

>95

Italy

6

<5

>95

>95
>95

>95

>95

>95

89

>95

12

50

>95

>95

IsraelIsle of Man

5
56

56

36

Guinea-Bissau
<5

5

<5

Guyana<5<5Guinea

69

94

>95

41

92

>95

Total clean
cooking
accessrate (%)

GuatemalaGuamGrenadaGreenland

GreeceGibraltar

Country

Rural clean
cooking
accessrate (%)

Total clean
cooking
accessrate (%)

<5

<5

68

>95

>95

54

>95

>95

>95

57

90

<5

7

>95

>95

7

<5

27

<5

<5

18

91

>95

<5

7

93

>95

>95

86

>95

>95

>95

>95

>95

41

35

>95

>95

44

<5

61

<5

<5

42

93

>95

6

20

>95

>95

>95

>95

>95

>95

>95

>95

>95

62

69

>95

>95

71

7

75

<5

<5

68

92

>95

2010
Urban
clean
cooking
accessrate (%)

2000
Urban
clean
cooking
accessrate (%)

<5

<5

86

>95

>95

75

>95

>95

>95

91

93

23

14

>95

>95

18

<5

55

<5

<5

13

94

>95

Rural clean
cooking
accessrate (%)

<5

9

>95

>95

>95

85

>95

>95

>95

>95

>95

67

43

>95

>95

51

<5

71

<5

<5

45

91

>95

Total clean
cooking
accessrate (%)

2015

6

23

>95

>95

>95

93

>95

>95

>95

>95

>95

85

77

>95

>95

74

7

81

<5

<5

69

90

>95

Urban
clean
cooking
accessrate (%)

<5

<5

92

>95

>95

78

>95

>95

>95

>95

94

51

21

>95

>95

31

<5

68

<5

<5

14

94

>95

Rural clean
cooking
accessrate (%)

<5

10

>95

>95

>95

84

>95

>95

>95

>95

>95

80

49

>95

>95

57

<5

76

<5

<5

46

89

>95

Total clean
cooking
accessrate (%)

2018

6

24

>95

>95

>95

91

>95

>95

>95

>95

>95

91

81

>95

>95

76

7

83

<5

<5

70

88

>95

Urban
clean
cooking
accessrate (%)

<5

<5

95

>95

>95

78

>95

>95

>95

>95

94

68

28

>95

>95

41

<5

73

<5

<5

14

94

>95

Rural clean
cooking
accessrate (%)

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

163

53
<5
>95

Lao People’s Democratic
Republic

LatviaLiberia

53

41
82
>95
7

>95
23
67
91
<5

MonacoMongolia

Montenegro

MoroccoMozambique

>95

10

>95

>95

83

94

Mauritius
30

30

Mauritania

22

>95

Micronesia (Federated
States of)15

Marshall Islands

<5

>95

Mexico>95

Malta

Malaysia
56>95

Malawi<512<5Madagascar

Mali

<5

<5

Luxembourg

Maldives

>95

>95

>95

>95

>95

<5

47

>95

11

86

>95

Lithuania

Liechtenstein

Libya

17
<5

LesothoLebanon>95

Kyrgyzstan

Total clean
cooking
accessrate (%)

KuwaitCountry

Rural clean
cooking
accessrate (%)

Total clean
cooking
accessrate (%)

<5

81

47

<5

>95

34

45

91

14

<5

>95

<5

41

>95

<5

<5

>95

>95

<5

9

>95

<5

33

>95

<5

>95

63

35

>95

10

85

>95

42

53

>95

<5

93

>95

<5

<5

>95

>95

<5

31

>95

<5

72

>95

9

>95

75

50

>95

23

95

>95

68

71

>95

<5

>95

>95

11

<5

>95

>95

<5

73

>95

10

93

>95

2010
Urban
clean
cooking
accessrate (%)

2000
Urban
clean
cooking
accessrate (%)

<5

91

40

7

>95

5

52

>95

19

<5

>95

<5

90

95

<5

<5

>95

>95

<5

15

>95

<5

60

>95

Rural clean
cooking
accessrate (%)

<5

>95

58

44

>95

9

85

>95

43

63

>95

<5

>95

>95

<5

<5

>95

>95

<5

36

>95

5

76

>95

Total clean
cooking
accessrate (%)

2015

11

>95

69

62

>95

26

93

>95

68

83

>95

<5

>95

>95

10

<5

>95

>95

<5

78

>95

14

95

>95

Urban
clean
cooking
accessrate (%)

<5

94

37

11

>95

<5

53

>95

18

<5

>95

<5

>95

93

<5

<5

>95

>95

<5

18

>95

<5

65

>95

Rural clean
cooking
accessrate (%)

<5

>95

56

50

>95

8

84

>95

43

65

>95

<5

>95

>95

<5

<5

>95

>95

<5

39

>95

7

77

>95

Total clean
cooking
accessrate (%)

2018

12

>95

66

68

>95

27

92

>95

66

86

>95

<5

>95

>95

9

<5

>95

>95

<5

79

>95

17

95

>95

Urban
clean
cooking
accessrate (%)

<5

95

35

13

>95

<5

54

>95

19

<5

>95

<5

>95

93

<5

<5

>95

>95

<5

19

>95

<5

66

>95

Rural clean
cooking
accessrate (%)

164

Tracking SDG 7: The Energy Progress Report 2020

34
86
7

Namibia

Nauru

Nepal

6

<5
<5

<5
<5
93
58

Nicaragua

Niger

Nigeria

Niue

North Macedonia

80

Panama>95>95

PolandPortugal
>95
>95
64

Qatar

Republic of Korea

Republic of Moldova
>95

>95

>95

>95

>95

Philippines

Puerto Rico

61
57

43
38

72

33

>95

>95

66

>95

>95

68

Peru

6

>95

Palau

48

24

Pakistan

Paraguay

>95

Oman

Papua New Guinea>95

NorwayNorthern Mariana
Islands

55

34

92

>95

>95

>95

22

87

81

New Zealand

New Caledonia

>95

<5

Myanmar

Netherlands

Total clean
cooking
accessrate (%)

Country

Rural clean
cooking
accessrate (%)

Total clean
cooking
accessrate (%)

40

>95

>95

>95

>95

19

5

16

<5

54

>95

5

>95

>95

45

94

<5

<5

7

>95

>95

<5

26

9

<5

91

>95

>95

>95

>95

40

66

58

7

86

>95

35

>95

>95

65

90

<5

<5

44

>95

>95

21

90

41

10

>95

>95

>95

>95

>95

60

84

77

39

>95

>95

83

>95

>95

87

95

<5

6

69

>95

>95

66

91

75

26

2010
Urban
clean
cooking
accessrate (%)

2000
Urban
clean
cooking
accessrate (%)

86

>95

>95

>95

>95

20

13

29

<5

67

>95

11

>95

>95

39

89

<5

<5

8

>95

>95

11

24

12

<5

Rural clean
cooking
accessrate (%)

95

>95

>95

>95

>95

43

74

65

7

88

>95

40

>95

>95

66

86

5

<5

47

>95

>95

27

90

44

20

Total clean
cooking
accessrate (%)

2015

>95

>95

>95

>95

>95

63

90

84

39

>95

>95

86

>95

>95

91

>95

11

10

72

>95

>95

65

91

74

54

Urban
clean
cooking
accessrate (%)

92

>95

>95

>95

>95

23

25

35

<5

69

>95

16

>95

>95

33

86

<5

<5

9

>95

>95

15

25

12

5

Rural clean
cooking
accessrate (%)

>95

>95

>95

>95

>95

46

80

68

8

88

>95

44

>95

>95

65

84

10

<5

48

>95

>95

29

90

46

28

Total clean
cooking
accessrate (%)

2018

>95

>95

>95

>95

>95

67

93

86

38

>95

>95

87

>95

>95

93

>95

21

13

74

>95

>95

60

91

72

70

Urban
clean
cooking
accessrate (%)

94

>95

>95

>95

>95

27

36

38

<5

69

>95

20

>95

>95

29

84

<5

<5

9

>95

>95

18

23

12

7

Rural clean
cooking
accessrate (%)

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

165

86
95

Saint Kitts and Nevis

Saint Lucia

Saint Vincent and the
Grenadines

<5

<5

<5
>95

Sierra Leone

Singapore>95
21

South Sudan

Spain

Sri Lanka
12
78

Sudan

SurinameState of Palestine55<5South Africa

9<5Somalia>95

Slovenia

Solomon Islands>95

Slovakia

Sint Maarten (Dutch
part)

>95

>95

Seychelles

70

89

20

58

>95

<5

76

<5

40

>95

>95

>95

85

35
63

>95

SerbiaSaudi Arabia

>95

46

>95

78

>95

Senegal<5>95

Sao Tome and Principe

21

>95

Rwanda>95<5

Russian Federation

San Marino

>95
<5

>95

77
>95

Samoa

Total clean
cooking
accessrate (%)

59

8

14

>95

<5

29

<5

<5

>95

>95

>95

<5

>95

39

7

>95

<5

>95

12

>95

91

>95

<5

>95

55

87

32

20

>95

<5

77

<5

8

>95

>95

>95

<5

>95

67

35

>95

<5

>95

26

95

>95

>95

<5

>95

88

94

51

55

>95

<5

89

<5

38

>95

>95

>95

<5

>95

85

65

>95

<5

>95

57

>95

95

>95

<5

>95

>95

Urban
clean
cooking
accessrate (%)

Rural clean
cooking
accessrate (%)

Urban
clean
cooking
accessrate (%)

Romania

Total clean
cooking
accessrate (%)

Country

2010

2000

76

22

13

>95

<5

56

<5

<5

>95

>95

>95

<5

>95

44

7

>95

<5

>95

18

>95

>95

>95

<5

>95

78

Rural clean
cooking
accessrate (%)

92

44

26

>95

<5

83

<5

8

>95

>95

>95

<5

>95

67

27

>95

<5

>95

31

95

>95

>95

<5

94

80

Total clean
cooking
accessrate (%)

>95

62

63

>95

<5

93

<5

36

>95

>95

>95

<5

>95

85

49

>95

<5

>95

62

>95

>95

>95

<5

95

>95

Urban
clean
cooking
accessrate (%)

2015

84

35

18

>95

<5

61

<5

<5

>95

>95

>95

<5

>95

44

5

>95

<5

>95

24

>95

>95

>95

<5

95

61

Rural clean
cooking
accessrate (%)

94

50

31

>95

<5

85

<5

9

>95

>95

>95

<5

>95

66

23

>95

<5

>95

35

95

>95

>95

<5

90

75

Total clean
cooking
accessrate (%)

>95

66

69

>95

<5

94

<5

36

>95

>95

>95

<5

>95

84

41

>95

<5

>95

65

>95

>95

>95

<5

92

>95

Urban
clean
cooking
accessrate (%)

2018

89

43

23

>95

<5

63

<5

<5

>95

>95

>95

<5

>95

43

<5

>95

<5

>95

27

>95

>95

>95

<5

93

50

Rural clean
cooking
accessrate (%)

166

Tracking SDG 7: The Energy Progress Report 2020

87
>95
>95

58
>95
>95
94
>95

Tonga

Trinidad and Tobago

Tunisia

TurkeyTurkmenistan

<5
92
>95
>95

<5
>95

UgandaUkraineUnited Arab Emirates

United Kingdom ofGreat Britain andNorthern Ireland

United Republic of
Tanzania

United States ofAmerica84
17

Uzbekistan

Vanuatu
57

>95
>95

>95

>95

<5

>95

>95

95

<5

23

>95

>95

Uruguay

United States Virgin
Islands

31

TuvaluTurks and Caicos
Islands

<5

<5

5

87

85

>95

Togo

39

Tajikistan
63>95

Syrian Arab Republic

>95

>95

<5

>95

Switzerland

Timor-Leste>95

SwedenThailand

Total clean
cooking
accessrate (%)

Country

Rural clean
cooking
accessrate (%)

Total clean
cooking
accessrate (%)

5

71

>95

>95

<5

>95

>95

86

<5

13

>95

88

93

>95

49

<5

<5

50

24

>95

>95

>95

12

86

>95

>95

<5

>95

>95

95

<5

41

>95

95

>95

>95

55

<5

5

74

69

>95

>95

>95

39

>95

>95

>95

<5

>95

>95

>95

<5

44

>95

>95

>95

>95

85

8

12

87

95

>95

>95

>95

2010
Urban
clean
cooking
accessrate (%)

2000
Urban
clean
cooking
accessrate (%)

<5

74

>95

>95

<5

>95

>95

87

<5

17

>95

86

>95

>95

45

<5

<5

64

60

>95

>95

>95

Rural clean
cooking
accessrate (%)

9

86

>95

>95

<5

>95

>95

95

<5

42

>95

95

>95

>95

52

7

9

78

77

>95

>95

>95

Total clean
cooking
accessrate (%)

2015

29

>95

>95

>95

5

>95

>95

>95

<5

45

>95

>95

>95

>95

81

15

20

87

>95

>95

>95

>95

Urban
clean
cooking
accessrate (%)

<5

74

>95

>95

<5

>95

>95

87

<5

15

>95

84

>95

>95

43

<5

<5

70

70

>95

>95

>95

Rural clean
cooking
accessrate (%)

8

85

>95

>95

<5

>95

>95

95

<5

43

>95

95

>95

>95

50

9

12

79

81

>95

>95

>95

Total clean
cooking
accessrate (%)

2018

24

>95

>95

>95

7

>95

>95

>95

<5

42

>95

>95

>95

>95

79

20

26

87

>95

>95

>95

>95

Urban
clean
cooking
accessrate (%)

<5

73

>95

>95

<5

>95

>95

87

<5

14

>95

82

>95

>95

41

<5

5

73

75

>95

>95

>95

Rural clean
cooking
accessrate (%)

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

167

93

14
34

50
26
42
80
>95
10
82
78

Yemen

ZambiaZimbabwe

WorldCentral Asia andSouthern Asia

Eastern Asia and Southeastern Asia

Latin America & the
Caribbean

Northern America andEuropeSub-Saharan Africa

Western Asia andNorthern Africa

Oceania

Note:
Data source: Household Energy Database, WHO, January 2020.

>95

93

25

>95

93

65

58

76

88

38

38

13

>95

56

Source: World Health Organization

Total clean
cooking
accessrate (%)

40

68

<5

94

42

24

10

25

5

<5

42

5

87

77

89

12

>95

85

54

37

56

30

16

60

49

>95

96

>95

26

>95

95

77

72

81

81

37

95

79

>95

Urban
clean
cooking
accessrate (%)

Rural clean
cooking
accessrate (%)

Urban
clean
cooking
accessrate (%)

Viet Nam>95

Total clean
cooking
accessrate (%)

Venezuela (Bolivarian
Republic of)Country

2010

2000

36

79

<5

>95

52

29

15

29

5

<5

43

35

87

Rural clean
cooking
accessrate (%)

76

91

13

>95

87

62

44

60

29

15

60

59

>95

Total clean
cooking
accessrate (%)

96

>95

28

>95

95

82

78

82

78

32

94

82

>95

Urban
clean
cooking
accessrate (%)

2015

35

81

<5

95

57

37

22

33

5

<5

43

48

85

Rural clean
cooking
accessrate (%)

76

91

15

>95

88

67

49

63

29

13

60

64

>95

Total clean
cooking
accessrate (%)

96

>95

31

>95

94

84

82

83

75

28

94

82

>95

Urban
clean
cooking
accessrate (%)

2018

34

82

<5

94

60

42

28

37

5

<5

42

54

84

Rural clean
cooking
accessrate (%)

00

Azerbaijan

BahamasBahrain

90.6

91.4
28.1

BhutanBolivia (Plurinational
State of)
19.8

3.8

48.1

32.9

5.8

7.3

9.1

41.1

4.4

30

8.1

5.5

9.4

9

50.8

0.3

0

Bermuda70.3

2.1

Austria

Benin

26.2

Australia

34.6

8.4

Aruba

Belize0.2

Armenia

1.4

7.2

Argentina

5.6

11.1

Antigua and Barbuda

Belgium

00

Anguilla

Belarus1.7

0.2

Angola

59

0

73.4

Andorra

14.3

0.1

14.5

Barbados

18.7

0

American Samoa

Bangladesh

00.4

Algeria

37.1

14.9

41.4

2000
54.2

2010

Albania

20

2015
17.5

86.5

0.5

50.9

33.1

9.3

6.8

3.2

34.6

0

1.4

2.3

34.3

9.2

6.7

11.6

10.1

0.5

0.2

47.8

19.3

1.5

0.1

38.6

RenewableenergyAfghanistan

UN country name

13.4

83.4

0.5

45.6

38.7

9.6

7.3

3.6

32

0

1.4

1.9

33.2

9.5

6.5

12.5

11.2

0.6

0.2

56.2

19.1

1.8

0.1

37.2

24.7

2017

11.2

71.6

0.1

45.6

30.9

4.8

6.8

2.8

31.7

0

1.4

0.5

15.7

5.4

0.3

6

3.1

0

0.1

50.2

0.3

0

0

7.9

0

0

0

0

0

1.5

0.1

0

0

0

0

0

1.9

0.1

0

0

2.6

0

0

0

0

0

0

3.8

0

0

0

0

0

0.5

0

0

0

0

0

0

0.4

0.1

0

0

0

0

0

0

0

0

0

0

2.2

11.9

0

0

7.8

0.1

0.2

0

0.2

0

0

1.3

11.8

1.5

0

6.4

5.5

0

0

6

17.2

0

0

24.9

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.1

0

0

0

0

1.6

0

0

0

0

0

0

2

1.1

6.1

0

0.1

0

0

0

0

0

0

0

0

0

0

0

0

0.9

0

0.8

0

0

0

0

1.1

1.2

0

0

0

0.6

0.1

0

0

1.8

0.1

0.6

0

0

0

0

0

0

0

0

0

0

0

0

0.1

0

0

0

0

0

0

0

0

0

0

0

0

0

0.4

0

0

0.3

0

0

0

0

0

0.1

0.3

0

0

0

0

0

0

0

1.7

0

0

0

7.8

7.9

0

0.1

2

53.5

2.3

0.1

3.6

0

0

4.7

161.7

115

0.4

5.8

135.4

0

0

23.8

1.6

0

1.7

21.4

33.8

47.4

0

79.6

3.4

59.5

47.4

0.3

391.9

0

0.3

1.5

173.5

185.1

0

5.6

66.1

0

0

199.3

0

0

0.4

7.4

13.5

0

0

0

0

0

21.1

0.2

0

0

0

0

0.1

28.3

7.5

0

0.1

61.1

0

0

0

0

0

0

3.2

0

309.4

66.3

4.7

174.6

14.2

1393

686.9

11.9

1236.5

191.4

19.6

329.2

1093.43224.46.8

92.2

2335.7

3.9

1.4

397.3

8.6

0.5

1472.5

86.2

110.6

b

a

a

b

a

b

b

a

b

b

a

b

b

b

a

b

b

a

a

b

a

a

b

b

a

Solid
biofuels
2017

13.8

Liquidbiofuels
2017

0

Biogases
2017

0

Hydro
2017

0

Tide
2017

0

Wind
2017

0

Solar
2017

12.4

Geothermal
2017

0

Municipal
waste(renew)
2017

0

Electricity
consumption (1)
2017

12.2

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

This table, including the data contained in it, must not be reproduced, disseminated or transferred, in whole or in part, without IEA’s and UNSD’s written permission. The data in thistable sourced to the IEA is subject to the IEA’s terms and conditions. This notice and any sourcing statements included in this table must not be removed from the table.

Data provided by the IEA and UNSD

SDG 7.2 – RENEWABLE ENERGY

2017

168

Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

169

19.6

0
14.4

0
8

Brunei Darussalam

22.5
0

38.5
81.1
84.5
21.5
0

BurundiCabo VerdeCambodia

Cameroon

Canada

40.4

32.9
63.7

Costa Rica

Côte d'Ivoire
75.4

0

0

54.8

64.9

Cook Islands

Congo

5.4

Comoros

China, Macao Special
Administrative Region

0.8

12.3

27.9

0.2

China, Hong Kong Special
Administrative Region

46.4

0.6

China

27

28

29.6

Chile

81.6

79.8

48.3

31.4

Chad

78.6

68.5

Colombia

85.1
88.7

Central African Republic

Cayman Islands

92.6

93.2
21.2

81.5

85.4

Burkina Faso

Bulgaria

0.7

46.9

29.9

1

42.8

Brazil

2010
0

3

2015
64.9

38.3

1.2

64.8

44.9

28.8

7.4

0.8

12.2

25.1

85.4

76.4

0

21.4

78

64.9

26.3

91.2

72.7

17.7

0

1

43.7

28.4

25.3

RenewableenergyBritish Virgin Islands

19.4
36.6

Botswana0

2000

Bosnia and Herzegovina

Bonaire, Sint Eustatius andSaba

UN country name

2017
62.7

36.2

1.7

70

38.8

29.2

5.9

0.8

12.8

23.5

85.4

75.8

0

23.1

78.6

61.5

22.9

88.2

70

17

0

1.3

45.3

28.6

18.8

2.8

11.9

61.6

14.7

0

67

38.8

14.9

0.1

0.6

4.2

14.9

85.4

73

0

5.6

74.9

58

19.9

87.4

69.6

10.8

0

1

22.8

28.5

0

0

0

0

0

0.1

0

0

0.1

0

0

0

0

1.2

0

0

0

0

0

1.7

0

0

7.9

0

0

0

0

0

0

0

0

0

0.1

0.4

0.1

0

0

0

0.1

0

0

0

0

0

0.2

0

0

0

0

0

1.2

16.8

0

2.1

0

14.2

0

0

4.6

6.2

0

2.6

0

14.9

3.8

3.4

0

0.8

0.4

1.7

0

0

12.7

0

6.8

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2.5

0

0

0

0

0

0

1.2

1

0

0

0

1.1

0

0

2.7

0

0

0.9

0

0.2

1.4

0

0

0

0

1.7

1

0

0

0

0

1.8

1.3

0

0.1

0

0.2

0

0

0.2

0

0

1.1

0

0.1

0.4

0

0

0

2.2

0

0

0

0

0

0

0.6

0

0

0

0

0

0

0

0

0

0

0.4

0

0

0

0

0

0

0

0

0

0

0

5.8

0

0

0

0

0

0

0

0

0

0

0

0

0.3

0

0

0

0

0

4

35.5

0

2.5

0

176.2

2

0.5

4906.8

108.8

0

0.5

0

1183.7

11.6

9.7

0.2

0.5

0.7

14.5

0

0

1412.6

0

10

183.9

23.4

0

53.7

1.7

177.9

0

2.4

4686.8

147

60.7

12.8

0

402.3

230.3

160.4

1.4

48.5

110.6

47.5

0

0

1912.2

23.6

17.4

0

0

0

0

0

0

1.6

0

0.2

204.1

1.5

0

0

0

109.3

0

0

0

0

0

7

0

0

713.4

0

0.1

0

299.4

162.5

0.7

80.2

4.3

1216.9

34.6

388.5

76741.2

1095.1

71.1

17.5

5

7323.5

307.6

276.8

7

55.5

158.9

404.8

38.4

1.3

8915.6

82.6

146.2

4

b

b

a

b

a

b

a

b

b

b

a

a

a

b

b

b

a

a

a

b

b

a

b

b

b

a

Solid
biofuels
2017

0.1

Liquidbiofuels
2017

0

Biogases
2017

0

Hydro
2017

0.3

Tide
2017

2.3

Wind
2017

0

Solar
2017

0

Geothermal
2017

0

Municipal
waste(renew)
2017

0

Electricity
consumption (1)
2017

0.1

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

170

Tracking SDG 7: The Energy Progress Report 2020

97.9

Democratic People's Republicof Korea

Democratic Republic of the
Congo

2.8
52.2
31.7
9.3
23.8
9.9
72.8

Fiji

FinlandFranceFrench Guiana

French Polynesia

Gabon

1.4

Falkland Islands (Malvinas)

Faroe Islands

62.1

19.8

Estonia

95.6

76.8

Eritrea

Ethiopia

50.4

Equatorial Guinea

Eswatini

8.1
33.5

EcuadorEl Salvador

20

Dominican Republic

Egypt

11
19.1

Dominica

10.7

8.7

Czechia

31.4

5.9

CyprusDjibouti

6.4

3.1

Denmark

0.5

0.1

85.8

12.5

29.4

12

33.6

28

3.4

3.4

94.1

63.1

25.1

81.2

5.9

29.1

5.7

11.4

17

10.1

32.5

21.3

96.8

13.5

11

14.6

34.4

Curaçao

2000

Cuba

29.8

2010

26.8

2015
82

10.2

..

13.7

43.2

29.9

7.5

4.7

91.5

66.4

27.5

79

9.8

21.3

5.7

13

15

8.6

13.3

33.5

95.8

23.1

14.8

9.9

2.4

20.1

33.1

RenewableenergyCroatia

UN country name

2017
81.2

10.9

..

14.5

44.4

27

6

4.9

89.8

60.6

27

78.4

12

25.3

5.5

16.7

17

9.8

14.5

36.5

97.1

27.4

14.5

10.4

3.7

17.7

29.8

Final consumption of renewable energy (PJ)

79.7

0.4

..

7

32.9

20.3

0

1.3

87.7

56.5

25.3

78.4

10.3

11.5

3.4

4.3

13.6

4

14.5

20.2

94.7

14.7

10.4

1.3

0

14.7

0

0

..

2.4

1.7

0

0

0

0

0

0

0

0

0

0

0.1

0

0

0

1.6

0

0

1.3

0.6

0

2.9

0

0

..

0.3

0.4

0

0

0

0

0

0.4

0

0

0.2

0

0

0

0

0

1.6

0

0

1.3

0.6

0

0

1.5

9.8

..

2.4

6.3

6.7

3.9

0

1.9

4.1

0

0

1.6

6.6

1.8

12.2

2.7

5.8

0

0

2.5

12.7

0.4

0

0

0.1

0

0

..

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

..

1.2

2

0

2.1

3.6

0.1

0

1.2

0

0

0

0.3

0

0.5

0

0

9.4

0

0

0.1

1.1

3.4

0.1

0

0.7

..

0.6

0

0

0

0

0

0

0

0

0

0.7

0

0

0.3

0

0

0.8

0

0

0.6

5.5

0.3

0

0

..

0.1

0

0

0

0

0

0

0

0

0

6.4

0

0

0

0

0

0

0

0

0

0.1

0

0

0

0

..

0.5

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2.9

0

0

0.2

1.2

0

0

2.1

2.9

0.8

..

255

134.7

1.6

0.6

0

34.1

4.8

3.6

0

0.6

16.5

49.1

62.7

8.6

0.1

0

78.5

25.9

32

22.4

1.4

0.9

155.6

0

..

450.8

296.6

4.8

0

0

1460.7

15.9

28.1

17.6

3.8

8.7

76.3

20.1

33.6

0.1

0.9

120

999.8

37.1

110.6

4.9

0

54.6

0

0

..

146.2

17.7

0

0

0

0.1

0

0.1

0

0

0

0.2

0.6

0

0

0

10.1

0

0

13.8

0.4

0

0

195.3

7.6

..

5867.21011.9

23.7

9.5

0.5

1665

34.2

117.7

22.5

37

99.2

2266.8

498.6

248.5

1.6

6.5

571.3

1056.1252.2

1014.9

64

24.8

320.3

283.3

b

a

b

b

a

a

a

b

a

b

b

a

b

b

b

b

a

a

b

b

b

b

b

b

b

b

Solid
biofuels2017

0.6

Liquidbiofuels
2017

49.7

Biogases
2017

34.2

Hydro
2017

0

Tide
2017

0.1

Wind
2017

0.3

Solar
2017

2.1

Geothermal
2017

0

Municipal
waste(renew)
2017

9.1

Electricity
consumption (1)
2017

0.6

Heat raising
(2)
2017

0

Transport
(3)
2017

17.5

Total final energy
consumption (PJ)

Share in total final energy consumption (%)

2017

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

171

3.7
71.6

Germany

Ghana

2010
0
67.3

2.6
0
62.7
0

GrenadaGuadeloupe

Guam

Guatemala

Guernsey

13.5
75.4

30
76
55.2
5.2
60.7

GuyanaHaiti

Honduras

Hungary

Iceland

1.7
5.2

0.4
0.4
2
0
6
5.1
5.3

Iran (Islamic Republic of)

Iraq

IrelandIsle of Man

IsraelItaly

Jamaica
9.7

12.8

8.6

1.9

0.9

39.5

Indonesia

40.6

51.8
45.6

India

50.2

79

30.5

87.8

91.2

Guinea-Bissau

75.7

85.6

Guinea

0

3

10.5

10.5

11.1
10.1

7.5
12.8

Greenland

0

48.3

10.3

39.1

54.7

2015
13.4

16.6

3.7

2.2

9.1

0.8

0.9

35.5

34.5

77

15.5

52.6

76.1

25.6

86.9

78

0

63

1.3

..

12.3

13.1

17.2

0

40

14.2

28.7

51.3

RenewableenergyGreece047.3

Gibraltar

63.1

Georgia

2000

GambiaUN country name

2017
12.4

16.4

3.8

1.9

10.2

0.4

1

35

32.2

76.7

14.3

53.3

76.1

22.5

86.5

77

0

64.2

3

..

12.6

11.3

16.1

0

40

15.3

28.7

50.8

9

7.2

0.2

0

2.1

0.1

0.3

32.4

29.3

0

11.6

46.4

76

22.5

86.5

76

0

60.5

0

..

12.6

0

5.7

0

33.9

5.2

9

1.8

1.3

0

0

1.6

0

0

1.1

0.1

0.6

0.8

0

0

0

0

0

0

0

0

..

0

0

1.1

0

0

1.4

0

0

0.8

c

0

0.2

0

0

0

0

0.1

0.3

0

0

0

0

0

0

0

0

..

0

0

0.3

0

0

2

0

0.5

2.8

c

0.5

0.5

0.3

0.6

0.8

1.7

38.1

0.1

4.5

0.1

0

0

1

0

3.3

0

..

0

11

2.1

0

6.1

0.7

19

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

..

0

0

0

0

0

0

0

1

1.4

0.1

0

5.1

0

0

0

0.6

0

0.4

0.9

0

0

0

0

0

0.1

0

..

0

0

3

0

0

3.6

0.2

0.1

2.1

3.6

0

0.1

0

0

0

0.5

0

0.3

1.4

0

0

0

0

0

0.1

2.9

..

0

0

3.8

0

0

1.7

0.1

0

0.6

0

0

0

0

0

0.6

0

37.9

0.6

0.1

0

0

0

0

0

0.2

0

..

0

0

0.1

0

0

0.1

0.4

0

0.3

0

1.4

0.6

0

0

0

0

0

0.2

0

0

0

0

0

0

0

0

..

0

0.3

0

0

0

0.7

0

2

357

5.1

0

26.9

2.4

45.5

100.8

711.7

64.2

14.2

17.3

0.2

0.2

0

1.4

0

24.2

0.2

..

0

0.9

48.4

0

17.5

609.6

31.6

6.4

347.9

17

0

11.3

1.1

21.3

2272.96614.5

29.6

87

97.7

106.6

6.2

24.2

102.8

0

281.3

0

..

0.4

0

50.3

0

96.1

570

16

5.2

1.4

58.9

0

0

7.4

0

0.1

77.5

25.6

1

6.7

0

0

0

0

0

0

0

0

..

0

0

7.3

0

0

123.2

1

0

79.4

4648.2

573.9

2.4

445.6

827.4

6848.57004.422830.2

123.5

752.3

215.9

140.3

28.4

28

135.2

1.3

475.8

5.8

..

3

8

660.3

7.8

283.7

8541.3

169.3

10.3

b

b

b

a

b

b

b

b

b

b

b

b

b

a

a

a

a

b

a

a

a

b

b

b

b

b

a

Solid
biofuels
2017

0Liquidbiofuels
2017

0

Biogases
2017

0

Hydro
2017

0

Tide
2017

0

Wind
2017

0

Solar
2017

0

Geothermal
2017

0

Municipal
waste(renew)
2017

0

Electricity
consumption (1)
2017

50.8

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

2

Libya

19.6
1.7
44.4
20.4
16.2

Martinique

Mauritania

Mauritius

Mayotte
10

13.6

34

2.5

13.3

Malta

Marshall Islands

1.2

0

1.4
67.1

2.3

2

85.4

Malaysia

81.2

86.3

Mali

4.5

Malawi

3.7

21.5

52.3

1.5

88.6

53

5.7

33.1

64.9

25.6

0

48.3

76.5

Maldives

83.4
82.6

Madagascar

6.8

Luxembourg

17.2

90.8

Liberia

Lithuania

56.7

Lesotho

53.9

4.9

Liechtenstein

35.8

Lebanon

KuwaitLatvia0

Kiribati

81.6

56.5

Kenya

Lao People's Democratic
Republic

79

Kazakhstan

35.2

2.5

JordanKyrgyzstan

3

2.1
1.4

4.8

4.8

0

2000
3.8

2010

Jersey

6.3

2015
..

11.5

28.9

..

11.3

5.6

58.4

1.4

3.4

80.8

78.3

9.1

29

55.5

1.9

84

44.1

3.7

38.1

53.9

23.3

0

47.6

72.2

1.5

3.2

15.9

RenewableenergyJapan

UN country name

6.9

2017
..

9.7

23.3

..

11.8

7.4

58.6

1.2

5.2

75.9

82.6

15.4

33.6

55.3

1.8

85

38.7

3.3

42.6

45.9

24.5

0

45.8

71.8

1.6

5.1

16.9

..

7.8

22.3

..

11.4

0.3

55.2

0.9

0.1

69.2

81.5

2.8

21.7

6.2

1.8

84.9

33.5

2.4

31.6

37.6

0

0

44.6

68.4

0.1

0.9

0

..

0

0

..

0

1.7

0

0

0.8

0

0

3.1

1.2

0

0

0

0

0

0.3

0

0

0

0

0

0

0

0

..

0.2

0

..

0

0.4

0

0

0

0

0

1.4

0.8

0.8

0

0

0

0

1.5

0

0

0

0

0

0

0

0

..

0.9

0

..

0

0

3.4

0

4.2

6.7

1.1

1.4

2.8

35.6

0

0.1

5.2

0.5

8.4

8.2

24.5

0

0

1.3

1.4

0

0

..

0

0

..

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

..

0.1

0.6

..

0

0

0

0

0

0

0

4

6.2

0

0

0

0

0

0.3

0

0

0

0

0

0

0.5

0

..

0.7

0.5

..

0.4

4.9

0

0.3

0.1

0

0

1.9

0.3

12.7

0

0

0

0.5

0

0

0

0

1.2

0

0

3.6

0

..

0

0

..

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2

0

0

0

..

0

0

..

0

0

0

0

0

0

0

0.8

0.6

0

0

0

0

0

0.5

0

0

0

0

0

0

0

16.9

..

2.2

0.7

..

0

0.8

2.9

0.1

88.7

4.5

2.7

15.1

25.3

1.4

0

0.1

2.4

1.1

16.7

11.3

36.1

0

0

24.3

23.4

4.2

1

..

1.2

13.8

..

0.2

0.3

43.8

0.1

0

44.7

186.7

3.3

45.5

0.2

6

73.5

15.6

6.4

51.8

51.5

0.1

0

0.5

480.8

2.1

9.6

0

177.9

..

0

0

..

0

0.3

0

0

16.2

0

0

5.1

2.7

0

0

0

0

0

0.7

0

0.2

0

0

0

1.8

0

0

27.6

..

34.6

62.1

..

1.7

20.3

79.6

16

2012.7

64.8

229.3

151.6

219.1

3

340.5

86.5

46.4

225.3

162.4

137

148.1

692.4

1.2

703.8

1683.3273.3

6.1

10809.6

b

a

a

b

a

a

b

a

a

b

b

a

b

a

a

b

b

a

b

b

a

b

b

b

a

b

Solid
biofuels
2017

540.3

Liquidbiofuels
2017

0.1

Biogases
2017

0.1

Hydro
2017

1.8

Tide
2017

0.2

Wind
2017

0

Solar
2017

2.5

Geothermal
2017

0

Municipal
waste(renew)
2017

0.2

Electricity
consumption (1)
2017

2.1

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

172

Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

173

2000
32.2

70.4

Peru

66.4

Paraguay0

Palau

Papua New Guinea

51

Pakistan

27.7

0

Oman

Panama60.2

Norway0

North Macedonia

Northern Mariana Islands

0.6
19.4

Niue

58.4

Nicaragua
87.6

29

New Zealand

86.2

7.5

New Caledonia

Nigeria

1.8

Netherlands

Niger

0
88.3

36.1

Namibia

Nepal

80.2

Myanmar

Nauru

93.6

MozambiqueMontserrat

30.5

63.6

55.3

19.9

0

46.8

0

56.6

0

22.4

26.7

86.9

80.7

52.5

31.6

4.8

3.9

87.3

0.1

28.9

84.9

84.3

13.9

0

0

Montenegro

15.3

..

Morocco

4.5
49.1

5.7

Mongolia

1.8

9.4

2010

2

12.2

11.2

0

43

3.6

1.4

9.2

2015
25

61

50.9

21.2

0

45.2

0

58.5

0

24

22.4

82.3

78.9

48.6

31.1

5.1

5.8

85

0.1

28

70.6

79.1

RenewableenergyMicronesia (Federated Statesof)

MexicoUN country name

2017
27.7

60.1

49.7

22.8

0

41.4

0

61.2

0

19.1

22.4

82.5

79.5

47.2

30.4

5.1

6.5

76.6

0.8

28.1

60.6

59.5

10.4

0

38.1

3.5

1.6

9.5

13.4

42

46.3

7.5

0

38.9

0

4.7

0

12.3

0.5

82.3

79.5

42.3

8.4

0.3

2.1

70.8

0

9.6

56.3

41.5

7.9

0

22.7

2.6

1.2

2

2.4

0

0

0

0

0

2.8

0

0

0

0

0

0

0

0

0.7

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.2

0

0.3

0

0

0

0

0.2

0

0.4

2.1

0

0

0

0

0

0

0

0

0

11.6

15.8

2.3

14

0

2.3

0

51.7

0

5.6

0

0.3

0

1.2

14.5

3.6

0

3.7

0

18.4

4.3

18

0.6

0

14.1

0.1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.4

0

0

1

0

0.2

0

1

0

0.6

0

0

0

1.6

1.2

0.5

1.8

0

0

0

0

0

1.7

0

1.3

0.7

0

0.3

0

0

0.3

0

0.1

0

..

0

0.1

21.9

0

0

0

0.1

0.7

0.4

0

0.8

0.2

0

0

0.2

0

0

0.1

0.3

0

0

1.1

0

0

0

0

0

0

0.3

0

0

0

1.9

6

0

0.2

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.8

0

0

0

0

0

0

0

0

0.9

0

0

0

0

0

0

0

0

0

0

99.3

41.6

4.1

23

0

93.2

0

397.1

0

5.1

0

16

0

7

113.5

1.5

55.5

20.5

0

14

34.5

43

16.3

0

4.6

1.4

0

105.6

110.8

56.2

11.1

0

1401

0

42.1

0

9.8

0

4512.9

96.4

43.3

54

0.2

53.8

408.8

0

7.4

455.8

99.4

51.6

0

6.9

3.8

0

311.1

14.1

6.3

0

0

0

0

0

24.4

0

0

0

0

0

0

0.3

0

13.9

0

0

0

0

0

0.2

0

0

0

0

0.6

790.8

264

121.3

149.6

2.3

3609.2

770.6

757.9

1.1

77.9

0.1

5486.4

121.4

106.5

551.5

34.9

1895.2

560.8

0.5

76.3

809.4

239.6

653.4

0.3

30.2

147.8

1.4

4903

b

b

a

b

a

b

b

b

a

b

a

b

b

b

b

a

b

b

a

b

b

b

b

a

b

b

a

b

Solid
biofuels
2017

155.9

Liquidbiofuels
2017

0

Biogases
2017

0.4

Hydro
2017

0.3

Tide
2017

0.6

Wind
2017

0

Solar
2017

2

Geothermal
2017

0

Municipal
waste(renew)
2017

0

Electricity
consumption (1)
2017

6.2

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

3.3
90.7

5.7
11.7
16.4
3.5
86.7

RéunionRomania

Russian Federation

Rwanda

0.7
84.2
0.5

0.6
90.4
0.3
0

Seychelles

Sierra Leone

Singapore

Sint Maarten (Dutch part)

19.5
45

55.2

Slovenia

Solomon Islands

10.3

3.7
15.9

Slovakia

0

20.6

22.1

Serbia

50.3

47.5

0

43.8

Senegal0

54.7

Saudi Arabia

Sao Tome and Principe

36Saint Vincent and the
Grenadines
42.5

5.1

8.5

Samoa

1.3

2.6

2.6
0.6

Saint Pierre and Miquelon

1

9.2

24.1

Saint Lucia

7.1

16.4

0.7

Republic of Korea

Republic of Moldova

26.6

1.3
19.8

0

Qatar

Saint Kitts and Nevis

0

0.7

Portugal

Puerto Rico

Saint Helena

27.8

20.1
0.6

9.5

28.8

6.9

2000
34.8

2010

Poland

2015
48.5

20.8

13.4

0

0.6

77.9

1.4

21.2

40

0

40.2

26.9

4.5

0.7

2.6

1.7

12.6

86.7

3.2

23.7

..

24.7

2.7

0

1.8

27.2

11.9

25.9

RenewableenergyPhilippines

UN country name

2017
48.7

20.4

12.4

0

0.7

77.5

0.6

19.9

37.6

0

38.4

26.8

3.4

0.7

2.7

1.8

13.1

86.7

3.2

23.4

..

26.1

2.8

0

2.2

24.4

11.1

23.4

48.6

11.7

5.9

0

0.2

76.6

0

12.4

36.5

0

37.4

22.8

2

0.7

2.7

0

5.2

85.4

0.6

15.6

..

25.1

1.1

0

0

13

8

0

0.9

1.5

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1.3

..

0

0.5

0

0

1.7

0.9

0

0.3

0.9

0

0

0

0

0.2

0

0

0

0

0

0

0

0

0

0

0

0.1

..

0.1

0.1

0

0

0.2

0.3

0

5.8

3.5

0

0

1

0

7.2

0.8

0

1

2.7

1.4

0

0

0

0

1.3

2.6

3.8

..

0.8

0.2

0

0.3

2.7

0.3

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

..

0

0

0

0

0

0

0

0

0

0

0

0

0.4

0

0

0

0

0.1

0

0

0

1.3

5.3

0

0

2

..

0

0.1

0

1.2

5.6

1.5

0.1

0.7

0.5

0

0.1

0

0.2

0

0.3

0

0

1.3

0

0

0

0.5

2.5

0.1

0

0.5

..

0

0.5

0

0.8

1

0.1

0

1

0

0

0

0

0

0.1

0

0

0

0

0

0

0

0

0

0

0

0.1

..

0

0.1

0

0

0.1

0

0

0

0.1

0

0.4

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

..

0

0.3

0

0

0.2

0.1

0

13.3

21.6

0

3.3

0.6

0

25.5

1.6

0.4

0

0.2

0

0

0

0

0

1.1

419.4

59.6

..

1.1

62

0

1.1

65

67.7

3.2

26

23.5

0

0

42.5

0

44.2

47.1

0.3

0.8

0.9

0.1

0

0.1

0

0

68.5

102.1

148

..

31.4

71.1

0

0

79.9

226.7

226.2

0

2

6.8

0

0.2

0

0

0.3

0

0

0

0

0

0

0

0

0

0

47.6

13.9

..

0

22.5

0

0

10.8

27

19.4

6.6

202.5

417

7.9

498.6

55.5

5

351.6

129.5

4671

2.1

4

2.8

0.7

2.9

1.9

0.1

80.2

17525.4

947.8

..

125

5469.6

567.9

48.8

637.1

2890

1343.5

a

b

b

a

b

a

a

b

b

b

a

a

a

a

a

a

a

a

b

b

b

b

b

a

b

b

b

Solid
biofuels
2017

68.7

Liquidbiofuels
2017

0

Biogases
2017

2.3

Hydro
2017

0.3

Tide
2017

0.2

Wind
2017

0

Solar
2017

2.1

Geothermal
2017

0

Municipal
waste(renew)
2017

1.6

Electricity
consumption (1)
2017

16.9

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

174

Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

175

40
18.2

Suriname

SwedenSwitzerland

0.1
1

93.7

UkraineUnited Arab Emirates

United Kingdom of GreatBritain and Northern Ireland

United Republic of Tanzania
5.4

1.3

UgandaUnited States of America

093.9

Tuvalu0.1
0.7

Turks and Caicos Islands

7.4

88.3

3.7

0.1

2.9

91.6

0

0.5

0.1

TurkeyTurkmenistan

14.2

17.3

0.3
12.7

0.8
14.2

1

65.8

Tunisia

2.5

34.7

22.7

61.8

1.4

20.4

46

22.4

Trinidad and Tobago

77.1

0

Timor-Leste

Tonga

22

Thailand

Togo

62.4

Tajikistan

2

23.6

Sudan

Syrian Arab Republic

80.4

State of Palestine
61.3

14.1

17.5

14.4
61.8

7.9

..

64.2

..

South Sudan

10.1

93.6

2010

Sri Lanka

16

2015
9.1

83.6

8.5

0.1

4.1

89

8.2

0.6

0.1

13.3

12.6

0.3

1.9

70.9

18.2

22.7

48.1

0.6

23.9

53.1

22.7

63

11

52.9

16.3

26.2

9.7

94.5

Renewableenergy

Spain

93.3

South Africa

2000

Somalia

UN country name

2017
9.9

83.8

10

0.2

6.5

88.5

13.5

1

0.1

11.4

11.9

0.4

1.5

71

19

22.7

41.7

1.1

24.7

52.3

21.6

60.5

12.4

48.4

15.6

27.9

10

94.9

3.1

82.9

3.8

0.1

4.9

86.8

0

0.5

0.1

2.4

10.8

0.4

0.7

66.8

19

17.6

0

0.1

5.2

26.9

5

54.7

5.9

45.1

5.6

27.9

8.8

2.9

0

0.8

0

0.1

0

0

0

0

0.1

0

0

0

0

0

2.3

0

0

0.7

5

0

0

0

0

1.6

0

0

0.1

0

0.7

0

0

0

0

0

0

0.2

0

0

0

0

0

0.9

0

0

0.4

0.5

0

0

0

0

0.2

0

0

1.7

0.9

0.4

0

1.2

1.7

0

0

0

4.1

0

0

0

4.2

0

1.1

41.7

1

15.7

13.9

16.5

5.8

0

2.9

1.8

0

0.1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1.4

0

3.2

0

0.1

0

0.8

0

0

1.3

0.4

0

0

0

0

0.1

0

0

0.1

3.8

0

0

0

0.3

4.6

0

0.5

0.5

0

0.8

0.1

0.1

0

12.7

0.5

0

1

0.8

0

0.7

0

0

0.5

0

0

1.1

0.1

0.1

0

6.5

0.1

1.7

0.1

0.6

0.1

0

0

0

0

0

0

0

0

2.3

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.1

0

0.3

0

0

0

0

0

0

0

0

0

0

0

0

0.1

0

0

1.5

2.2

0

0

0

0

0.1

0

0

2260

6.4

315.4

2.4

28

9.9

0

0

0

258.4

1.7

0

0

4.3

0

109.4

46.8

2

125

260

3.8

30.4

1.6

14

266.8

0

26.2

1847.2

612.3

141.2

1.9

96.7

484.9

0

0

0.4

214

38.5

0.5

0

66.4

0.8

539.3

0

0.2

50.6

350.1

1.1

287.6

6.8

190.3

188.5

5.5

240.6

107.3

1599.1

0

44.2

0

3.7

0

0

0

0

6.1

0

0

0

0

0

74.6

0.1

0

12.6

73.5

0

0

0

0

58.8

0

0.5

0

57574.1

738.4

5017.72062.7

1984.4

559

0.1

1.3

752.6

4195.5

337.5

128.9

1.8

99.5

4.3

3187.1

112.5

197.3

760.9

1307.1

23

526

68

422.2

3292.7

19.8

2684

113.1

b

b

b

b

b

a

a

a

b

b

b

b

a

b

a

b

b

b

b

b

b

b

a

b

b

b

b

a

Solid
biofuels
2017

0Liquidbiofuels
2017

0

Biogases
2017

0

Hydro
2017

0

Tide
2017

0

Wind
2017

0

Solar
2017

0

Geothermal
2017

0

Municipal
waste(renew)
2017

0

Electricity
consumption (1)
2017

94.9

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

2000

34.6
0.4

48.7
14.4

58
0

Vanuatu

Venezuela (Bolivarian
Republic of)Viet Nam

Wallis and Futuna Islands

19.9
38.4

8.4

6.1

Eastern Asia (M49)

South-eastern Asia
(MDG=M49)

Western Asia (M49) andNorthern Africa (M49)

Western Asia (M49)

23.2

Eastern Asia (M49)
and South-eastern Asia
(MDG=M49)

Latin America and the
Caribbean (MDG=M49)

43

28

Europe (M49)

3.7

7.4

Northern America (M49)

Southern Asia (MDG=M49)

7.3

Northern America (M49) andEurope (M49)

Central Asia (M49)

7.4

37.8

10

17.2

World

Central Asia (M49) andSouthern Asia (MDG=M49)

16.3

69.3

Zimbabwe

1

Zambia

4.5

6.2

31.7

10.5

13.6

34.1

3.1

30.6

28.5

10.8

9.1

82.2

92.4

1.2
89.9

Yemen

11.5

38.4

1.7

0.8

0
52.8

Uzbekistan

0

2010

38.8

3.9

2015
3.9

5.5

29.3

11

13.9

29.9

3.1

27.2

28.1

13.2

10.7

12

17

81.6

88

2.4

0.6

30.7

13.7

36.4

1.8

58.9

RenewableenergyUruguay

United States Virgin Islands

UN country name

3.5

2017
3.8

5.3

29

11.6

14.4

28.1

3.4

25.8

29.4

13.5

11.6

12.5

17.3

83.3

84.5

4.9

0.7

32

14.8

36.1

2.4

60.2

0.9

2.8

23.9

3.8

7

25.7

0.1

23.3

15.8

6

3.4

4.7

10.8

79.5

75

2.7

0

21.4

2.1

33.2

0

41.5

0

0

1.1

0.1

0.3

0

0

0

3.3

1

2.7

1.9

1

0.3

0

0

0

0

0

0.8

0

1.7

0

0

0.2

0.3

0.3

0

0

0

0

0.5

0.1

0.3

0.2

0

0

0

0

0

0

0

0

0

1.3

1.3

3.3

4.1

4

1.6

3.3

1.8

9

3.1

3.3

3.2

3.3

3.5

9.5

0

0.5

10.5

12.7

1

2.4

11.1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.3

0.3

0

1

0.8

0.4

0

0.4

0.8

1.6

1.4

1.5

0.9

0

0

0

0

0

0

0.8

0

5.6

0.5

0.4

0.1

1.7

1.4

0.3

0

0.3

0.3

0.7

0.5

0.6

0.7

0

0

2.1

0.2

0

0

0.3

0

0.4

0.6

0.4

0.4

0.5

0.5

0

0

0

0.1

0.1

0.1

0.1

0.2

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.3

0.1

0.2

0.1

0

0

0

0

0

0

0

0

0

309.1

397.7

748.7

5619.2

6366.8

912.9

115.7

1036.1

2611.73939.33558.47533.418470.7

15.2

37.6

2

0

279.9

155

0.1

21.5

38.5

289.2

749.4

4276.44979.49255.89088.82.7

9091.53665

4206.62248.76456.941312.6

329.5

297.3

2.6

0

569.4

25.3

0.8

0.2

75.8

0

5.8

6.4

190.1

248.3

438.9

25.2

4.9

29.2

804.3

829.3

1699

2514.83821.7

1

0.1

0

0

0

0

0

0.6

2.9

0

16065.5

21662.2

17968.1

93843.6111811.735700.1

3612.439312.5

24087.2

66660.3

64911

131571.3

367161.2

415.1

396.4

94.2

0.2

2656

1219.6

2.4

915.9

194.7

1.8

c

c

c

c

c

c

c

c

c

c

c

c

c

b

b

b

a

b

b

a

b

b

a

Solid
biofuels
2017

0.1

Liquidbiofuels
2017

0

Biogases
2017

0

Hydro
2017

3.5

Tide
2017

0

Wind
2017

0

Solar
2017

0

Geothermal
2017

0

Municipal
waste(renew)
2017

0

Electricity
consumption (1)20170Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

176

Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

177

56.1
16.8

13.1
48

11.4

83.8

23.9

43.4

60.5
25.2

Oceania (M49)

Oceania (M49) excluding
Australia and New Zealand(M49)

Australia and New Zealand(M49)

Least Developed Countries(LDCs)

Small island developing
States (SIDS)

Landlocked developing
countries (LLDCs)

Africa (M49)

Asia (M49)

11.2

18.3
8.7
83.3

Southern Africa (M49)

Southern Europe (M49)

Western Africa (M49)

Middle Africa (M49)

32.3

88

Micronesia (M49)

South America (M49)

5.1

Melanesia (M49)

15.4

54.5

Eastern Europe (M49)

16.6

4.3

Eastern Africa (M49)

Northern Europe (M49)

87.8

Central America (M49)

Polynesia (M49)

16.2

18.1

82

15.4

12.2

33.5

15.7

19.1

78.4

5.5

43.3

5.7

87.2

17.7

Caribbean (M49)

14.2

11.7
23.4

Americas (m49)

42.5

17.5

75.6

11.3

38.6

12.7

70.7

14.9

2000
72.3

2010

Sub-Saharan Africa (M49)

2015
77.2

18.1

11.5

32.6

12.9

25.7

77.9

5.9

39.8

6.3

84.2

16.5

20.1

15.5

15.9

54.6

43.5

17.9

72.7

12.2

35.8

13.5

68.5

10.2

RenewableenergyNorthern Africa (M49)

UN country name

9.8

2017
76.9

17.3

11.5

34.2

13.1

27.1

82.4

6.7

38.5

6.4

82.8

17.3

20.7

16.5

16

54.4

44

18

70.8

12.4

34.7

13.7

68.5

76.2

7.6

10.2

16.7

6.3

11.8

79.3

5.3

34.5

3.4

79.4

12.9

18.4

6.8

10.3

52.6

39.5

15.8

67.5

5.9

30.7

7.2

66.6

0

1.3

0

4.7

0

1.7

0

0

0

0.3

0

0

1

2.9

0.2

0

0.1

0.6

0

0.1

0

0.1

0

0

0.5

0

0

0

0.6

0

0

0

0.1

0

0

0

0.1

0.2

0

0.1

0

0.1

0.2

0

0.1

0

0.6

3

0.3

11.6

5.6

8

3

0

3

2.2

3.1

2.9

0.7

4.9

3.2

1.5

4.3

1

3.2

3.2

3

3.2

1.6

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2.7

0.5

0.9

0

3.2

0

0

0.1

0.3

0.1

0.7

0.4

1.2

0.7

0.2

0

0.2

0

1.2

0.1

1.1

0.1

0

1.8

0.6

0.3

1.1

0.5

0.1

1.4

0.1

0.1

0

0.3

0.2

0.4

1.1

0.1

0

0.2

0

1.1

0.3

1

0.1

0

0.3

0

0

0

0.5

0

0

0.7

0

0.3

0.5

0

0.1

0.4

0.1

0

0.1

0

0.8

0.6

0.8

0.1

0

0.2

0

0

0

0.8

0

0

0

0

0

0

0

0

0

0

0

0.1

0

0

0

0

0

47.9

842

33.9

2293.711347.2

66.9

0.2

7.4

659.4

185.7

279.9

16.3

6242.47660.7

416.3

410.5

36

353.9

221

8.6

229.8

329.1

5500

828.1

303.1

2682

1

1111

1716.8

0.7

65.3

923.2

4247.6780

203

5913.518637.4

12225.2

3837.4310.9

7362.2

239.1

67

306.1

11767

460.4

0

142

0.6

802.2

0

183.3

0

0

0

126.2

1.3

0.9

1.5

2503.7

464.6

5

17.7

2.3

0.2

9.7

0

9.6

4.7

0.7

7217.610452.82923.516892.2

159753.32164.214188.926748.5

5352.86126.71068.388998.2

167189.723254.8

9699.7

1945

10898.2

3775.9217.93993.717658.1

5596.7

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

Solid
biofuels
2017

88.7

Liquidbiofuels
2017

0

Biogases
2017

0

Hydro
2017

0.1

Tide
2017

0.3

Wind
2017

0

Solar
2017

1.2

Geothermal
2017

0

Municipal
waste(renew)
2017

0

Electricity
consumption (1)
2017

8.2

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

25.4
5.7
48
4.8

Eastern Asia (MDG)

Western Asia (MDG)

Oceania (MDG)

Caucasus and Central Asia
(MDG)

2010
11.2

4.2

38.6

3.9

11.5

70.4

5.4

9.6

2015
4

35.8

3.7

11.6

68.3

4.8

11.5

22.4

14.2

Renewableenergy
23.5

15

2017
4.3

34.7

3.5

12.1

68.3

4.6

12.1

22.5

0.6

30.7

0.8

4

66.3

3.4

4.6

16.3

0

0

0

0.1

0

0

1.7

0.6

0

0

0

0.4

0

0

0.3

0.2

3.7

3

1.2

4.3

1.7

0.8

3.2

3.7

0

0.1

0.4

1.1

0.1

0.3

1.4

0.7

0

0.3

0.4

1.7

0.1

0.1

0.7

0.8

0

0.6

0.6

0.5

0.1

0

0.1

0.3

0

0

0

0

0

0

0.2

0

151.1

8.6

264.1

5063.4

357.5

61.9

8326.310145.9

1358.9

25.8

67

244.2

4801.512054.6

172.9

6896.234396.4

344.5

5.9

0

5.1

221

4.9

0.5

2550.91262.1

19705.74203.1

217.9

14837

83033.9

18184.1

5070.7146794.6203302.1

NOTES
Allocation of renewable electricity and heat to final energy consumption.
To establish the contribution of each technology to the final consumption, the aggregated figures for electricity and commercial heat have to be allocated to the relevant technology. This can bedone based on the proportions exhibited in production data, attributing the losses proportionally (GTF 2013). For instance, if total final consumption table reports 150 TJ for biogases, while total final
consumption of electricity is 400 TJ and heat 100 TJ, and the share of biogases in total electricity output is 10 percent and 5 percent in heat, the total reported number for biogases consumption will be
195 TJ (150 TJ+400TJ*10%+100TJ*5%).

DEFINITIONS
Final consumption of renewable energy(1) Electricity consumption: Covers final consumption of renewable electricity in all sectors excluding transport(2) Heat raising: Covers final consumption of renewable energy for heat raising purposes (excluding electricity) in manufacturing, construction and non fuel mining industries, household, commerce andpublic services, agriculture, forestry, fishing and not elsewhere specified.
(3) Transport: Covers final consumption of renewable energy (including electricity) in the transport sector.

0

0

0

0

0

0

0

0

1252.5

c

c

c

c

c

c

c

c

c

Solid
biofuels2017

0.6

Liquidbiofuels
2017

0.1

Biogases
2017

1.1

Hydro
2017

2.3

Tide
2017
0

Wind
2017

2.2

Solar
2017

1.1

Geothermal
2017

1.6

Municipal
waste(renew)
2017

6

Electricity
consumption (1)2017

REFERENCE
a. Source: Energy Balances, UN Statistics Division (2019)b. Source: IEA (2019), World Energy Balances
c. Sources: IEA (2019), World Energy Balances; Energy Balances, UN Statistics Division (2019)

7.2
72.5

Sub-Saharan Africa (MDG)

7.2

Developed regions (MDG)

Northern Africa (MDG)

6.7
32.8

Developing regions (MDG)

2000

Western Europe (M49)

UN country name

Total final energy
consumption (PJ)

Heat raising
(2)
2017

Final consumption of renewable energy (PJ)
Transport(3)
2017

Share in total final energy consumption (%)

2017

178

Tracking SDG 7: The Energy Progress Report 2020

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

179

2.4
12.2
4.9

21.8
5.6
..
7.6

BermudaBhutanBolivia (Plurinational State of)

Bonaire, Sint Eustatius and Saba

Bosnia and Herzegovina

7.5

..

9.3

7.3

5.1

5.6

7.5

4.4

3.4

10.5

3.3

3.3

2.3

6.4

Belize

5.8
3.9

Benin

6.4

Belgium

3.6

Bangladesh
3.8

11.2

Bahrain

13.7

2.8

BahamasBelarus

12.8

Azerbaijan

Barbados

6.7
3.9

Aruba

Austria

6.8

Armenia

Australia

5.4
7.9

4.3

4.7
9.4

Antigua and Barbuda

Argentina

..
3.6

..
2.8

3.2

..

..

3.6

3.1

2.8

Anguilla

..
4.5

..

American Samoa

Angola3.6

Algeria

Andorra1.7
4.5

Albania

2010

6.7

..

5.0

10.5

..

8.8

5.5

4.7

6.5

3.6

3.1

9.9

2.7

3.7

3.6

5.1

3.4

5.2

4.3

3.5

..

3.5

..

..

4.2

2.9

2.2

2015

Energy intensity (MJ/USD 2011 PPP)
2000

Afghanistan

UN country name

6.9

..

4.9

9.7

..

9.2

5.5

4.8

6.5

3.3

2.9

9.1

2.6

3.8

3.5

4.8

3.4

5.2

4.3

3.2

..

3.4

..

..

4.1

2.9

1.9

2017

-0.2%

..

-1.3%

-5.7%

0.5%

2.5%

-2.3%

-1.3%

-5.9%

1.5%

-0.6%

-0.6%

1.8%

-12.6%

0.1%

-1.4%

1.6%

-5.4%

-0.9%

2.6%

..

-3.4%

..

..

0.2%

-3.7%

5.0%

2000-2010

-2.3%

..

0.2%

-2.9%

..

-1.1%

1.5%

-3.6%

-2.8%

-3.8%

-1.6%

-1.3%

-4.0%

2.3%

-1.7%

-2.8%

-15.5%

-0.7%

0.2%

-0.7%

..

1.8%

..

..

2.8%

-1.2%

-4.4%

2010-2015

1.4%

..

-0.5%

-3.7%

..

2.5%

0.6%

1.0%

0.6%

-5.0%

-3.4%

-4.1%

-1.3%

1.6%

-1.0%

-2.3%

0.4%

-0.3%

-0.5%

-3.1%

..

-0.6%

..

..

-1.2%

0.2%

-7.0%

2015-2017

Compound annual growth rate of Energy intensity (%)

b

b

a

b

a

b

b

a

b

b

a

b

b

b

a

b

b

a

b

b

b

a

SourceThis table, including the data contained in it, must not be reproduced, disseminated or transferred, in whole or in part, without IEA’s and UNSD’s written permission. The data in thistable sourced to the IEA is subject to the IEA’s terms and conditions. This notice and any sourcing statements included in this table must not be removed from the table.

Data provided by the IEA and UNSD

SDG 7.3 – ENERGY EFFICIENCY180

Tracking SDG 7: The Energy Progress Report 2020

3.4

2.5
2.1
..

Comoros

Congo

Cook Islands

5.0
4.3
22.5
4.4
7.9

Croatia

Cuba

Curaçao

CyprusCzechia

3.1

3.2

Colombia

5.8

1.3

China, Macao Special
Administrative Region

Côte d'Ivoire

3.1

2.5

China, Hong Kong Special
Administrative Region

Costa Rica

2.8

10.2

China

6.4

3.6

20.4

2.3

4.4

6.3

3.2

..

2.6

0.6

1.7

8.4

3.9

3.5

5.2

2.2

7.4

Central African Republic
4.8

7.2

Cayman Islands

7.9

5.0

Chile

2.0

Canada

3.2
6.2

Chad

6.6
9.2

Cameroon

2.7

Burundi
8.5

12.0

Burkina Faso

Cambodia

6.6

Bulgaria

Cabo Verde

6.6
6.5

10.8

Brunei Darussalam

9.1

..
4.3

..

3.9

3.7

3.9

British Virgin Islands

4.3

Brazil

2010

5.5

3.2

20.5

1.9

4.0

5.4

2.9

..

4.3

2.7

2.6

0.7

1.6

6.8

3.7

2.7

7.3

2.0

7.7

5.1

5.8

2.8

8.5

6.0

6.4

3.7

..

4.1

3.4

2015

Energy intensity (MJ/USD 2011 PPP)
2000

Botswana

UN country name

5.3

3.3

17.5

1.8

3.9

5.0

2.8

..

4.8

3.1

2.5

0.7

1.4

6.1

3.9

3.3

6.7

2.0

7.6

4.8

5.8

2.9

8.7

5.7

6.0

4.9

..

4.1

3.3

2017

-2.2%

-1.9%

-1.0%

-6.1%

-1.3%

0.9%

0.4%

..

4.1%

1.0%

-2.0%

-7.3%

-3.9%

-1.9%

-2.1%

-7.3%

-3.2%

1.0%

-1.6%

-2.8%

-3.1%

1.5%

-2.7%

-0.1%

-4.8%

1.7%

..

-0.1%

-2.2%

2000-2010

-3.0%

-2.3%

0.1%

-3.2%

-2.0%

-3.1%

-1.9%

..

6.9%

-0.9%

-0.3%

3.9%

-1.0%

-4.2%

-1.0%

-4.7%

6.8%

-1.9%

-0.6%

0.4%

-1.4%

-2.7%

-1.4%

-1.8%

-0.7%

-3.4%

..

1.0%

-0.1%

2010-2015

-1.8%

0.3%

-7.5%

-2.9%

-1.1%

-3.8%

-3.0%

..

5.2%

7.4%

-2.1%

0.0%

-6.1%

-5.2%

2.4%

8.9%

-4.3%

-1.0%

-0.7%

-3.1%

0.2%

1.6%

1.4%

-2.3%

-3.3%

16.0%

..

0.1%

-2.2%

2015-2017

Compound annual growth rate of Energy intensity (%)

b

b

b

b

b

b

b

b

a

b

a

b

b

b

a

a

a

b

b

b

a

a

a

b

b

b

b

SourceCHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

181

5.0

3.4
7.2
4.6
..

4.0
7.5
5.0
..

Fiji

FinlandFranceFrench Guiana

4.9
8.4
4.7
6.2
..
4.2
..
3.0

Gabon

GambiaGeorgia

Germany

Ghana

Gibraltar

GreeceGreenland

Grenada

3.4

..

3.6

..

4.2

4.1

5.0

4.4

..
8.5

..
2.8

French Polynesia

..

..

..

..

14.8

Faroe Islands

Ethiopia

7.8

5.0

2.6

4.6

Falkland Islands (Malvinas)

6.6
25.1

Eswatini

Equatorial Guinea
5.2

1.4

El Salvador

9.0

4.0

Egypt

Estonia

3.3

Ecuador

Eritrea

3.5
3.7

2.9

4.4

Dominica
4.0

3.5

Dominican Republic

4.8

3.3

19.5

5.6

3.5

Denmark
2.9

21.6

Democratic Republic of the Congo

5.7

Djibouti

6.9

2010

3.0

..

3.7

..

3.7

3.6

5.8

4.6

6.7

..

..

4.2

6.3

4.8

..

..

10.8

4.7

6.3

4.4

2.0

3.9

3.5

3.6

2.5

3.6

2.8

2.6

19.5

3.0

2015

Energy intensity (MJ/USD 2011 PPP)
2000

Democratic People's Republic of
Korea

UN country name

2.9

..

3.7

..

3.3

3.5

5.6

4.4

6.3

..

..

4.0

6.1

4.2

..

..

9.7

4.1

6.1

4.3

1.8

3.7

3.8

3.5

2.3

3.6

2.6

2.6

19.0

5.8

2017

1.4%

..

-1.5%

..

-3.8%

-1.2%

-5.1%

-1.0%

11.6%

..

..

-0.8%

-0.5%

-1.6%

..

..

-5.1%

-2.8%

-1.4%

-0.4%

5.9%

1.4%

1.3%

-1.1%

-4.1%

1.9%

-1.5%

-0.3%

-1.0%

-1.8%

2000-2010

-2.6%

..

0.5%

..

-2.5%

-2.8%

3.1%

0.6%

-4.4%

..

..

-1.9%

-2.4%

7.1%

..

..

-6.1%

-1.2%

-4.2%

-2.7%

-5.0%

-3.3%

-1.0%

0.3%

-3.0%

0.8%

-9.9%

-4.7%

0.0%

-12.0%

2010-2015

-1.5%

..

-0.5%

..

-6.1%

-1.7%

-1.8%

-1.7%

-3.2%

..

..

-2.5%

-1.6%

-6.7%

..

..

-5.4%

-7.0%

-1.8%

-0.8%

-5.7%

-2.3%

3.6%

-2.0%

-2.9%

0.0%

-5.2%

-0.2%

-1.5%

38.0%

2015-2017

Compound annual growth rate of Energy intensity (%)

a

b

b

b

b

a

b

b

b

a

b

a

b

b

a

b

b

b

b

a

a

b

b

b

Source182

Tracking SDG 7: The Energy Progress Report 2020

4.7
..

4.2
..

Guatemala

Guernsey

3.7
..
4.5
3.5
6.9
5.1
..

IrelandIsle of Man

IsraelItaly

JamaicaJapan

Jersey

8.7
5.5
5.5
9.6
4.4
6.1
5.1

Kenya

Kiribati

KuwaitKyrgyzstan

Lao People's Democratic Republic

LatviaLebanon

5.5

3.8

Iraq

10.1

4.6
4.6

5.9

Iran (Islamic Republic of)

Kazakhstan

3.4

5.3

Indonesia

Jordan

4.3

6.5

India

5.0

3.8

4.9

3.8

7.6

6.0

7.4

8.1

8.8

4.4

..

..

3.0

3.9

6.4

4.2

5.3

17.8

5.7
13.3

Iceland

5.9

10.6

Hungary

5.7
5.8

GuyanaHonduras

9.7

Guinea-Bissau

Haiti

13.7
7.9

8.7
12.8

10.2

Guinea

..

..

..

..

2010

Guam

2000

4.5

3.9

4.4

8.7

5.4

6.3

7.9

7.9

4.6

..

3.8

4.8

3.1

3.5

..

2.0

3.7

7.6

3.5

4.7

16.0

4.3

6.4

10.3

6.4

11.8

7.1

..

4.5

..

..

2015

Energy intensity (MJ/USD 2011 PPP)

Guadeloupe

UN country name

4.8

3.8

5.4

7.7

5.3

6.3

7.6

8.2

4.8

..

3.7

4.8

3.0

3.3

..

1.8

4.3

7.1

3.5

4.2

13.9

4.2

6.0

10.4

6.4

10.8

5.9

..

4.6

..

..

2017

-2.9%

-2.0%

-1.3%

-2.3%

0.9%

3.0%

-0.8%

-1.3%

-2.3%

..

-1.0%

-4.0%

-0.2%

-0.5%

..

-2.3%

0.4%

0.7%

-2.3%

-1.9%

2.9%

-1.4%

0.2%

6.5%

-2.1%

-0.6%

-1.7%

..

1.2%

..

..

2000-2010

3.6%

-4.5%

3.0%

2.7%

-2.1%

-3.3%

-0.3%

-2.1%

1.3%

..

-3.9%

0.6%

-2.0%

-3.9%

..

-7.9%

-1.4%

3.5%

-3.6%

-2.7%

-2.1%

-2.9%

1.5%

-0.5%

-4.2%

-1.5%

-4.0%

..

-1.0%

..

..

2010-2015

3.2%

-1.7%

10.9%

-6.0%

-0.4%

0.2%

-2.1%

1.7%

1.5%

..

-1.2%

0.1%

-1.1%

-2.9%

..

-4.2%

8.5%

-3.2%

-0.9%

-4.6%

-6.6%

-0.4%

-3.2%

0.0%

0.4%

-4.4%

-9.0%

..

1.2%

..

..

2015-2017

Compound annual growth rate of Energy intensity (%)

b

b

a

b

b

a

b

b

b

b

b

b

b

b

b

b

b

b

b

b

b

b

a

a

a

b

SourceCHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

183

4.6
..

5.6
..

Libya

Liechtenstein

3.0

..

New Caledonia
6.1

4.7

Netherlands
6.6

9.3

Nepal

Nicaragua

17.1

Nauru

New Zealand

3.8

Montserrat

8.9

..

Montenegro

Namibia..

Mongolia

Myanmar

9.0

Micronesia (Federated States of)

3.5

5.8

29.4

4.0

MexicoMozambique

7.9
5.4

..

MayotteMorocco

4.1
4.5

3.2

Mauritius

..

5.4

5.5

..

4.5

8.0

8.8

3.6

3.1

13.3

3.4

..

..

2.8

3.7

..
3.9

11.7

Mauritania

Marshall Islands

2.8

3.1

5.1

4.8

Martinique

3.0
10.5

Malta

Malaysia
2.4

5.4

Malawi

3.5

6.6

Madagascar

Mali

6.7

Luxembourg

Maldives

3.8
6.9

4.5

7.0
3.9

Lithuania

17.5

10.7

14.4
13.0

2010

Liberia

2000

5.4

5.4

..

3.8

7.4

4.7

3.3

2.9

14.2

3.2

..

4.5

5.7

6.2

3.6

..

2.5

4.0

..

11.4

1.8

2.8

3.2

4.6

4.2

7.6

2.9

3.8

..

6.9

16.8

8.0

2015

Energy intensity (MJ/USD 2011 PPP)

LesothoUN country name

5.0

5.0

..

3.7

7.8

3.5

3.5

3.2

13.2

3.2

..

4.2

5.9

6.1

3.4

..

2.3

4.6

..

11.0

1.6

2.6

3.3

4.2

4.1

8.9

2.9

3.8

..

4.9

17.6

8.0

2017

-1.3%

-1.9%

..

-0.3%

-1.5%

-6.4%

-0.4%

-10.0%

-7.6%

-0.5%

..

..

-1.3%

-2.4%

0.2%

..

-1.3%

-0.3%

..

1.1%

0.1%

-2.3%

2.6%

-0.5%

-3.1%

0.2%

-0.3%

-4.3%

..

-2.1%

3.0%

-2.9%

2000-2010

0.0%

-0.5%

..

-3.4%

-1.5%

-12.0%

-1.5%

-1.4%

1.4%

-1.2%

..

-3.9%

-6.2%

6.6%

-2.2%

..

-1.8%

1.4%

..

-0.5%

-10.1%

0.2%

1.1%

-2.0%

-2.8%

2.1%

-5.1%

-3.6%

..

8.4%

-0.8%

-5.8%

2010-2015

-3.2%

-3.1%

..

-1.1%

2.9%

-13.0%

2.2%

4.7%

-3.8%

0.0%

..

-3.3%

1.7%

-1.0%

-3.6%

..

-4.3%

7.6%

..

-1.6%

-3.2%

-4.7%

0.2%

-4.8%

-0.8%

8.0%

-1.4%

0.1%

..

-15.4%

2.5%

0.3%

2015-2017

Compound annual growth rate of Energy intensity (%)

b

b

b

b

a

b

b

b

b

b

b

a

b

b

a

a

b

a

a

b

a

a

b

b

b

a

a

Source184

Tracking SDG 7: The Energy Progress Report 2020

..

3.3

..
3.0
3.1
..
2.8
4.2
5.9

Saint Lucia

Saint Pierre and Miquelon

Saint Vincent and the Grenadines

Samoa

Sao Tome and Principe

RwandaSaint Kitts and Nevis

8.4

Russian Federation

Saint Helena

8.7

5.2

3.9

3.1

..

2.7

2.6

..

6.0

4.2

6.5

Réunion12.5..

Romania

9.3

7.0

5.2

0.2

3.4

5.1

3.2

2.8

..

Republic of Moldova

2.6
6.2

11.8

7.1
8.1

0.1

Puerto Rico

Republic of Korea

3.9

Portugal

Qatar

5.1
6.6

PolandPeru

Philippines

3.8
3.0

Paraguay

3.1

Palau
6.5

12.3

PakistanPapua New Guinea

5.5

Oman

Panama

5.7
4.9

3.2

Norway

11.8

..
4.0

..

5.1

4.2

North Macedonia

7.0
6.6

Northern Mariana Islands

..
6.4

Niue

7.2
9.7

Nigeria

2010

4.7

4.2

2.8

..

2.6

2.4

..

4.8

8.0

3.3

..

7.7

6.6

6.2

0.4

3.3

4.1

3.1

2.7

3.1

5.4

2.2

10.2

4.5

6.3

3.6

..

4.2

..

5.9

6.9

2015

Energy intensity (MJ/USD 2011 PPP)
2000

Niger

UN country name

4.5

4.1

3.3

..

2.3

2.4

..

4.4

8.3

3.0

..

7.3

6.4

5.9

0.4

3.3

4.2

3.1

2.6

3.7

5.1

2.1

11.0

4.4

6.4

3.7

..

4.2

..

6.4

6.6

2017

-1.3%

-0.9%

1.1%

..

-1.5%

-1.4%

..

-3.4%

-3.6%

-4.4%

..

-2.4%

-1.5%

-3.1%

7.2%

-1.2%

-2.6%

-4.5%

-0.7%

-1.3%

-0.4%

-1.7%

-0.4%

-1.2%

6.0%

-0.4%

..

-2.2%

..

-3.8%

-0.3%

2000-2010

-2.2%

1.8%

-2.0%

..

-0.7%

-1.7%

..

-4.2%

-1.5%

-4.7%

..

-3.7%

-1.2%

3.5%

14.3%

-0.5%

-4.1%

-0.9%

-0.7%

-1.5%

-2.9%

-3.8%

-3.0%

-1.6%

2.1%

-2.4%

..

-4.0%

..

-2.3%

-0.3%

2010-2015

-1.2%

-1.4%

7.9%

..

-4.6%

0.0%

..

-4.9%

1.9%

-3.4%

..

-2.5%

-1.2%

-2.7%

0.0%

-0.6%

0.7%

-0.5%

-1.5%

8.5%

-2.3%

-0.9%

4.2%

-0.7%

0.6%

1.1%

..

0.0%

..

4.5%

-1.7%

2015-2017

Compound annual growth rate of Energy intensity (%)

a

a

a

a

a

a

b

b

b

b

b

a

b

b

b

b

b

a

b

a

b

b

b

b

b

b

SourceCHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

185

..

..
8.8
5.9
8.7
..

Singapore

Sint Maarten (Dutch part)

Slovakia

Slovenia

Solomon Islands

Somalia

5.2..

Thailand

Timor-Leste

3.6
25.9

Tunisia

TurkeyTurkmenistan..

4.2

Trinidad and Tobago

Turks and Caicos Islands

3.2
18.0

Tonga

14.5

5.2

Tajikistan

Togo

5.7

..

18.8

3.4

3.9

20.0

3.2

16.4

0.5

5.4

6.6

7.3
12.2

Switzerland

Syrian Arab Republic

5.3
2.5

6.1
2.9

Suriname

Sweden

4.4
3.9

7.2
5.5

3.5

2.4

3.5

..

9.0

..

8.0

Sudan

3.4
3.5

State of Palestine

Spain

Sri Lanka..
4.2South Sudan

10.5

2.6

3.7

Sierra Leone

South Africa

7.7

5.5

3.3

6.7

4.7

5.4

9.5

Serbia13.1

4.2

Senegal

6.2

Seychelles

4.6

2010

3.9

13.9

3.0

3.8

18.4

3.0

13.3

0.9

5.4

5.1

4.1

2.1

4.2

3.3

4.7

3.8

2.1

3.3

1.7

7.8

..

6.0

4.6

4.5

9.3

2.8

7.0

2.9

6.1

4.1

5.8

2015

Energy intensity (MJ/USD 2011 PPP)
2000

Saudi Arabia

UN country name

4.0

12.3

3.0

3.8

17.7

3.7

12.9

0.9

5.1

5.2

4.5

2.0

4.4

1.9

4.3

3.8

2.0

3.3

1.5

8.0

..

5.5

4.5

4.4

..

3.1

6.5

3.2

6.1

3.6

5.5

2017

..

-3.2%

-0.7%

-0.7%

1.0%

-0.1%

1.2%

..

0.4%

-7.4%

-1.0%

-1.4%

-1.4%

-3.4%

-4.8%

0.1%

-3.4%

-1.7%

..

-1.5%

..

-0.7%

-1.3%

-4.6%

..

-3.4%

-5.2%

-4.6%

-3.4%

1.1%

3.1%

2000-2010

..

-5.9%

-2.9%

-0.7%

-1.6%

-1.1%

-4.0%

14.1%

-0.1%

-2.0%

-9.0%

-3.0%

-4.6%

-3.3%

1.3%

1.4%

-2.5%

-1.3%

..

-2.9%

..

-5.8%

-2.6%

-4.1%

..

1.3%

-1.9%

-2.9%

-2.0%

-2.5%

-1.4%

2010-2015

1.5%

-6.0%

1.3%

0.4%

-1.9%

10.1%

-1.7%

3.9%

-2.6%

1.2%

4.3%

-2.6%

2.4%

-24.4%

-3.6%

-0.4%

-1.9%

-0.2%

-6.5%

1.1%

..

-4.3%

-1.3%

-0.2%

..

5.6%

-4.0%

5.6%

0.2%

-6.5%

-2.8%

2015-2017

Compound annual growth rate of Energy intensity (%)

a

b

b

b

b

a

b

a

b

b

b

b

b

b

b

a

b

b

b

b

a

b

b

b

a

a

b

b

b

Source186

Tracking SDG 7: The Energy Progress Report 2020

7.5
6.1

23.8
4.1
4.8
11.1
7.4

UkraineUnited Arab Emirates

United Kingdom of Great Britain
and Northern Ireland

United Republic of Tanzania

United States of America

3.9

11.0
5.3

4.1
6.7
17.6
6.1
7.1
7.6
5.3

Latin America and the Caribbean(MDG=M49)

Central Asia (M49) and Southern
Asia (MDG=M49)

Central Asia (M49)

Southern Asia (MDG=M49)

Eastern Asia (M49) and Southeastern Asia (MDG=M49)

Eastern Asia (M49)

South-eastern Asia (MDG=M49)

4.5

7.2

6.6

5.7

4.0

5.1

7.5

6.2

5.6

6.0

6.7

Northern America (M49) andEurope (M49)

5.9

16.6

Europe (M49)

6.6

8.0

3.1

..

6.3

Northern America (M49)

12.0

World

Wallis and Futuna Islands

Zimbabwe..

Viet Nam
2.9

5.9

Venezuela (Bolivarian Republic of)

11.9

6.1

Vanuatu

Zambia3.9

4.0

Uzbekistan

Yemen

14.7

34.1

Uruguay

6.3

..
3.0

..
3.0

United States Virgin Islands

3.7

5.4

15.5

10.2

3.4
12.6

2010

Uganda

2000

4.0

6.1

5.7

4.9

8.9

5.1

3.8

4.5

5.6

4.9

5.2

13.7

7.8

1.9

..

5.9

5.2

3.9

9.2

3.1

..

5.4

6.3

3.0

5.4

12.2

9.8

3.8

2015

Energy intensity (MJ/USD 2011 PPP)

TuvaluUN country name

3.9

5.6

5.3

4.5

8.3

4.7

3.7

4.4

5.3

4.8

5.0

13.0

8.1

2.0

..

5.6

6.0

3.7

7.2

3.0

..

5.1

5.7

2.8

4.5

11.2

9.5

3.7

2017

-1.7%

-0.6%

-0.7%

-1.3%

-4.6%

-1.6%

-0.3%

-1.6%

-1.9%

-1.8%

-1.2%

3.3%

-3.8%

0.8%

..

0.8%

0.4%

-0.3%

-8.1%

-0.2%

..

-2.0%

-3.8%

-2.5%

2.8%

-4.2%

-2.1%

1.5%

2000-2010

-2.0%

-3.4%

-3.1%

-1.8%

-4.2%

-2.0%

-0.9%

-2.5%

-2.2%

-2.4%

-2.2%

-3.8%

-0.6%

-9.6%

..

-1.4%

-3.8%

0.0%

-9.0%

0.7%

..

-2.4%

-3.4%

-4.3%

-0.2%

-4.7%

-0.8%

-0.5%

2010-2015

-1.2%

-4.0%

-3.6%

-3.8%

-3.0%

-3.9%

-1.1%

-0.8%

-2.4%

-1.5%

-2.2%

-2.6%

1.7%

4.4%

..

-3.0%

7.6%

-2.9%

-11.0%

-1.0%

..

-2.6%

-4.8%

-3.2%

-8.5%

-4.2%

-1.4%

-1.6%

2015-2017

Compound annual growth rate of Energy intensity (%)

c

c

c

c

c

c

c

c

c

c

c

b

b

b

b

b

a

b

b

b

b

b

b

b

a

a

SourceCHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

187

8.6
4.7

Western Africa (M49)

Western Europe (M49)
6.3

3.9

Southern Europe (M49)

Developing regions (MDG)

4.2
10.1

Southern Africa (M49)

Polynesia (M49)

South America (M49)..

Northern Europe (M49)

5.9

4.3

6.4

3.6

8.6

4.0

..

5.8
4.2

7.1
5.0

Micronesia (M49)

Middle Africa (M49)

5.6

7.9

9.5

8.4

Eastern Europe (M49)
5.9

11.2

Eastern Africa (M49)

..
4.1

8.9

12.2

Central America (M49)

5.5

6.2

5.9

8.3

3.4

5.8

5.8

5.6

Melanesia (M49)..
4.0

Caribbean (M49)

6.6
6.5

Americas (m49)

7.1

Africa (M49)

Asia (M49)

12.5

Landlocked developing countries(LLDCs)Australia and New Zealand (M49)
7.8

6.7

Oceania (M49) excluding Australia
and New Zealand (M49)

4.1

5.9

Oceania (M49)

Small island developing States(SIDS)

6.7

Least Developed Countries (LDCs)

7.5
5.8

9.6

Sub-Saharan Africa (M49)

3.8

4.9

4.5
3.9

Northern Africa (M49)

4.6

Western Asia (M49)

4.3

2010

5.3

3.8

5.7

3.3

7.4

3.9

..

3.3

6.1

7.9

5.3

6.9

8.3

3.7

..

5.0

5.4

5.6

7.2

3.3

5.4

5.1

5.3

5.1

6.7

3.9

4.5

4.4

2015

Energy intensity (MJ/USD 2011 PPP)
2000

Western Asia (M49) and Northern
Africa (M49)

UN country name

5.0

3.6

6.0

3.3

7.5

3.9

..

3.2

6.2

7.9

4.9

6.9

7.9

3.4

..

4.8

5.0

5.7

7.0

3.2

5.3

4.8

5.0

4.9

6.8

3.9

4.4

4.2

2017

-0.7%

-1.0%

-2.8%

-0.8%

-1.6%

-0.5%

..

-1.8%

-2.1%

-0.6%

-0.4%

-3.5%

-2.5%

0.2%

..

-1.7%

-0.6%

-1.7%

-4.0%

-1.9%

-3.0%

-1.4%

-0.4%

-1.4%

-2.4%

-0.3%

0.8%

0.5%

2000-2010

-2.2%

-2.6%

-2.3%

-1.5%

-2.9%

-0.3%

..

-4.2%

1.2%

-1.1%

-1.4%

-2.6%

-2.6%

-2.1%

..

-1.9%

-2.7%

-1.0%

-3.0%

-0.9%

-1.2%

-2.5%

-1.3%

-2.5%

-2.1%

0.5%

-1.5%

-0.9%

2010-2015

-2.9%

-1.7%

2.2%

-0.5%

0.9%

0.0%

..

-1.8%

0.3%

-0.2%

-3.1%

0.3%

-2.5%

-3.3%

..

-1.9%

-3.4%

0.2%

-1.4%

-0.3%

-1.1%

-2.5%

-2.9%

-2.5%

0.6%

-0.1%

-1.6%

-1.3%

2015-2017

Compound annual growth rate of Energy intensity (%)

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

c

Source188

Tracking SDG 7: The Energy Progress Report 2020

3.7
7.3
8.0

9.5
9.4
4.3
5.9
16.3

Northern Africa (MDG)

Sub-Saharan Africa (MDG)

Eastern Asia (MDG)

Western Asia (MDG)

Oceania (MDG)

Caucasus and Central Asia (MDG)
7.8

5.3

4.6

6.6

6.6

3.8

4.8

2015

7.4

5.0

4.4

6.0

6.7

3.8

4.7

2017

-5.7%

-0.4%

1.3%

-1.6%

-2.5%

0.2%

-1.7%

2000-2010

-3.1%

-1.3%

-1.5%

-3.8%

-2.0%

0.5%

-2.5%

2010-2015

-2.1%

-2.9%

-1.5%

-4.7%

0.4%

0.1%

-1.6%

2015-2017

Compound annual growth rate of Energy intensity (%)

c

c

c

c

c

c

c

SourceNOTES
Allocation of renewable electricity and heat to final energy consumption.
To establish the contribution of each technology to the final consumption, the aggregated figures for electricity and commercial heat have to be allocated to the relevant technology. This can bedone based on the proportions exhibited in production data, attributing the losses proportionally (GTF 2013). For instance, if total final consumption table reports 150 TJ for biogases, while total final
consumption of electricity is 400 TJ and heat 100 TJ, and the share of biogases in total electricity output is 10 percent and 5 percent in heat, the total reported number for biogases consumption will be 195
TJ (150 TJ+400TJ*10%+100TJ*5%).

DEFINITIONS
Final consumption of renewable energy(1) Electricity consumption: Covers final consumption of renewable electricity in all sectors excluding transport(2) Heat raising: Covers final consumption of renewable energy for heat raising purposes (excluding electricity) in manufacturing, construction and non fuel mining industries, household, commerce andpublic services, agriculture, forestry, fishing and not elsewhere specified.
(3) Transport: Covers final consumption of renewable energy (including electricity) in the transport sector.

REFERENCE
a. Source: Energy Balances, UN Statistics Division (2019)b. Source: IEA (2019), World Energy Balances
c. Source: IEA (2019), World Energy Balances; Energy Balances, UN Statistics Division (2019)

9.1

5.6

4.9

5.5

3.7

2010

6.5

2000

Energy intensity (MJ/USD 2011 PPP)

Developed regions (MDG)

UN country nameCHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

189

9.92

2.43

BurundiCôte d’Ivoire

52.19

Cambodia

Cameroon

Congo

Comoros
0.15

3.38

1.02

22.21

90.01

China

75.39

238

Chile

Colombia

0.02
106.3

0.44

Chad

3.9

2.02

Central African Republic
3.13

658.16

Cabo Verde

7.95

0.78
3.08

0.87
67.44

13.43

25.75

2.21
1.32

139.83

1.91

123.38

12.99

0.12

BrazilBurkina Faso

0.03
123.58

Botswana

5.13

22.35

4.78
0.09

Bolivia (Plurinational State of)Benin

Bhutan0.02
548.94

0.17

Belize10.92

179.81354.05204.310.01

0.03

166.943.64

0.1

486.23

16.42

20.33

560.050.02

623.160.02

316.460.01

210.49

7.48
0.08

0.18

Barbados

Bangladesh

0.02

1.5

490.09

19.09

0.01

49.35

2017

0.02

75.96

22.75

600.8

6.88

0.02

0.87

4.75

2015

Bahamas2.92

Armenia

Azerbaijan

89.85

Argentina
182.97

1.02

4.69

Anguilla

Antigua and Barbuda

0.02
0.05

Angola

35.43

2010

International Commitments (2017 USD Millions)

0.39

0.02

2000

Algeria

Afghanistan

Country

Data provided by IRENA and OECD

SDG 7.A – INTERNATIONAL FINANCIAL FLOWS

190

Tracking SDG 7: The Energy Progress Report 2020

1.46

60.21

Iran (Islamic Republic of)

Iraq

2.25

474.55Indonesia

India

153.2845.13

302.37126.24

2.28

0.81
32.16

Honduras

1.16

Haiti

0.02

Guyana0.21

9.3

Guinea-Bissau

GuineaGuatemalaGrenada

Ghana

8.1
24.12

0.2

369.38882.31361.38

47.54

1.44

1.17

0.02

1.69

59.2

6.59

111.790.28

414.12800.33240.59

25.51

3.29

0.12

0.83

0.71

7.69

29.19

4.07

Georgia

0.11

0.05

392.5

479.05

24.8

12.8

6.04

Gabon

26.46
1828.16

Gambia1.67

315.9890.35

Ethiopia

Fiji

1.02

14.11

0.05

Eswatini

Eritrea

75.14
0.02

55.08

280.01Equatorial Guinea

El Salvador

996.34

30.44

Egypt

2720.13

2.15
10.37

Ecuador

0.07

33.61

76.69

1.68

10.77

3.75

Dominican Republic

Djibouti

42.7

2.35

Dominica

12.19

Democratic Republic of the Congo
0.6

108.39243.76

2017

12.95

0.4

Democratic People’s Republic of Korea

74.53

421.83

7.39

0.78

4.05

0.09

Cuba

2015

Costa Rica

2010
17.73

2000

International Commitments (2017 USD Millions)

Cook Islands

CountryCHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

191

Lesotho

0.04

3.44

Mali

9.24

6.08

81.01

137.04

65.97
0.18

Niger

129.280.03

Nicaragua

10.36
58.06

22.72

14.9

11.42

Nepal

2.76

36.59

125.8551.35

116.81

New Caledonia

8.79

45.88

0.11

56.75

62.05

Nauru

Namibia

93
0.09

0.04

Mozambique

8.2

Myanmar

0.26

Morocco228.840.13

1.94

Montserrat

77.43

0.87

Mongolia

11.7

1.23

Micronesia (Federated States of)
5.03

487.2746.12

Mexico

18
0.34

3.98

9.2

Mauritius

40.58

25.75

0.02

0.05

3.71

26.28

45.35

0.03

632.651.22

288.75146.59

393.1

0.86

2017

200.680.12
1.99

Mauritania

4.05

0.02

9.4

Marshall Islands

2.36

4.79

Maldives

0.17

136.56

Malaysia
0.14

5.24
61.37

6.67

Malawi244.25Madagascar
14.64

0.04

Lebanon

Liberia

1.63

Lao People’s Democratic Republic
35.99

0.02
84.69

1.52

526.3641.72

162.11

59.75

2015

10.35

Kyrgyzstan
8.27

Kiribati

709.68
0.96

0.09

1.34

Kenya

6.65

0.17

2010

Kazakhstan

5.03

2000

International Commitments (2017 USD Millions)JordanJamaicaCountry

192

Tracking SDG 7: The Energy Progress Report 2020

Timor-Leste

Thailand

4.9

4.03

Tajikistan
0.16

5.05
6.34

83.48

Syrian Arab Republic

Suriname

Sudan

0.44

54.31

0.18

0.03

22.42

State of Palestine

1.35

1.57
0.03

Sri Lanka

43.13

0.07

701.6

254.99South Sudan

South Africa

6.86
0.31
0.38

9.09

0.01

2

3.03

9.54

79.25

1.98

535.64

1.94

288.59

0.01

0.01

27.23

206.68

0.29

25.51

0.02

156.730.36

0.93

Somalia

Solomon Islands

Sierra Leone

Seychelles

Senegal24
260.87

41.58

1.07

Sao Tome and Principe

3.66
1729.61

0.04

0.12

2017
5075.65

31.39

0.01
0.35

0.21

Samoa
0.15

0.01

Saint Lucia

Saint Vincent and the Grenadines

1.37

2.05

1.55

22.27

82.02

8.59

Saint Helena

Rwanda0.15

11.61

Philippines
7.16

7.64

Peru

Réunion

0.09
1.05

Paraguay

8.95

46.49

Papua New Guinea

Panama3945.01

0.01

44.87

0.56

258.46

2015

2010

5.07

0.04

2000

International Commitments (2017 USD Millions)

Palau

Pakistan

Niue

Nigeria

CountryCHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

193

2015

127.88Tunisia

Turkey

1.44
0.01
0.04

Yemen

ZambiaZimbabwe

66.98

Western Asia and Northern Africa

Sub-Saharan Africa

Source: International Renewable Energy Agency, Organisation for Economic Co-operation and Development

Oceania

148.99Eastern Asia and South-eastern Asia

8.88

1856.15

1949.56

719.3
915.8

571.89393.624601.49

10051.18

384.420.3

92.01

1243.43

0.87

1.09

8.68

Central Asia and Southern Asia

182.38Latin America and the Caribbean

Northern America and Europe

1363.86

0.01

Viet Nam

World

0.82

0.2

Venezuela (Bolivarian Republic of)

VanuatuUzbekistan

Uruguay

United Republic of Tanzania

Uganda88.04

5149.82

1273.75

693.115077.872522.28

14804.87

1720.64

6.17

7.1

0.27

202.2435.81

571.327893.082915.671643.133812.664562.5421398.39

5.86

135.01

0.01

24.04

17.58

240.16

55.96

25.62

87.36

8.38

28.6

546.49Tuvalu0.55

0.06

Turkmenistan
26.19

382.66

4.88

19.86

0.13

8.63

2017

393.25276.495.48
128.36

4.32

Tonga
13.86

2010
4.64

2000

International Commitments (2017 USD Millions)

Togo

CountryACKNOWLEDGMENTS
PARTNERSHIPThe Energy Progress Report is a product of exceptional collaboration among the five SDG 7 custodian agencies,
specially constituted in a Steering Group:International Energy Agency (IEA)

World Bank (WB)International Renewable Energy Agency (IRENA)

World Health Organization (WHO)

United Nations Statistics Division (UNSD)

The Steering Group was supported by the SDG 7 Technical Advisory Group composed as follows.


African Development Bank (AfDB)

UAE (Ministry of Foreign Affairs)



Clean Cooking Alliance

United Nations Association of China

Denmark (Ministry of Foreign Affairs)

United Nations Children's Fund (UNICEF)

ENERGIA

European Commission

United Nations Department of Economics andSocial Affairs (UN DESA)FIA Foundation



United Nations Development Programme (UNDP)

Food and Agricultural Organization (FAO)Germany (Federal Ministry for Economic
Cooperation and Development)

United Nations Economic Commission for Africa(UNECA)





Hivos

United Nations Economic Commission for Asia andthe Pacific (ESCAP)International Institute for Applied Systems Analysis



United Nations Economic Commission for Latin
America and the Caribbean (ECLAC)

International Labour Organization (ILO)

Islamic Development Bank

United Nations Economic Commission for Western
Asia (ESCWA)Kenya (Ministry of Energy & Petroleum)

Latin American Energy Organization (OLADE)

United Nations Economic Programme for Europe(UNECE)

Norway (Ministry of Foreign Affairs)

United Nations Environment Programme (UNEP)

Pakistan (Ministry of Foreign Affairs)

United Nations Framework Convention on Climate
Change (UNFCCC)

Renewable Energy Policy Network for the 21ST
Century (REN 21)



United Nations Human Settlements Programme(UN-Habitat)

Sustainable Energy for All (SEforALL)

TERI School of Advanced Studies

United Nations Industrial Development
Organization (UNIDO)The Netherlands (Ministry of Foreign Affairs)

The United Nations Office of the High
Representative for the Least Developed Countries,
Landlocked Developing Countries and Small Island
Developing States (UN -OHRLLS)

United Nations Institute for Training and Research(UNITAR)

Vienna University of Technology

194

Tracking SDG 7: The Energy Progress Report 2020

The financial and technical support of the Energy Sector Management Assistance Program (ESMAP) is gratefully
acknowledged. ESMAP — a global partnership between the World Bank and 19 development partners and philanthropic
foundations to help low and middle-income countries to increase their know-how and institutional capacity to achieveenvironmentally sustainable energy solutions for poverty reduction and economic growth. ESMAP is funded by Austria(Ministry of Finance), Canada (Global Affairs Canada), ClimateWorks Foundation, Denmark (Ministry of Foreign
Affairs), European Union, Germany (BMZ and BMU), Iceland (Ministry of Foreign Affairs), Italy (AICS), Japan (Ministryof Finance), Luxembourg (Ministry for Sustainable Development and Infrastructure), the Netherlands (Ministry ofForeign Affairs), Norway (Ministry of Foreign Affairs/NORAD), the Rockefeller Foundation, Sweden (SIDA), Switzerland(SECO), and the United Kingdom (DFID, BEIS, and FCO).

AUTHORSHIPThe technical co-leadership of the project by the custodian agencies was the responsibility of Laura Cozzi (IEA), Rabia
Ferroukhi (IRENA), Leonardo Souza (UNSD), Elisa Portale (WB), and Heather Adair-Rohani (WHO).
The chapter on electrification was prepared by the World Bank (Juliette Besnard, Paul P. Mathew, Sharmila Bellur),with contributions from IRENA (Adrian Whiteman, Gerardo Escamilla) and GOGLA (Silvia Francioso) on off-griddata and UNHCR (Theresa Beltramo) on forcibly displaced people data.

The chapter on clean cooking was prepared by the World Health Organization (Heather Adair-Rohani, Jessica
Lewis, Itzel Lucio Martinez), with substantial contributions from University of Exeter (Oliver Stoner).



The chapter on renewable energy was prepared by the International Energy Agency (Paolo Frankl, Heymi Bahar,
Yasmina Abdelilah, Pharoah Le Feuvre, Francois Briens, Roberta Quadrelli, Francesco Mattion, Faidon Papadimoulis)
and the International Renewable Energy Agency (Rabia Ferroukhi, Emma Åberg, Anindya Bhagirath, Emanuele
Bianco, Celia García-Baños, Carlos Guadarrama, Diala Hawila, Michael Renner), with substantial contributions
from UNSD (Leonardo Souza, Agnieszka Koscielniak).



The chapter on energy efficiency was prepared by the International Energy Agency (Kevin Lane, Jeremy Sung,
Alyssa Fischer, Joe Ritchie, Giulia Ragosa, Roberta Quadrelli, Francesco Mattion, Faidon Papadimoulis), with
contributions from UNSD (Leonardo Souza, Agnieszka Koscielniak).



The Outlook chapter was led by the International Energy Agency (Arthur Contejean, Kieran McNamara, Timothy
Goodson, Amrita Dasgupta), with the renewable energy section jointly prepared with International Renewable
Energy Agency (Adrian Whiteman, Emma Åberg, Elisa Asmelash, Gerardo Escamilla, Ricardo Gorini, Sandra Lozo,
Gayathri Prakash, Costanza Strinati, Nicholas Wagner).



The chapter on indicators and data was jointly prepared by all custodian agencies under the coordination of theInternational Energy Agency (Roberta Quadrelli, Francesco Mattion, Faidon Papadimoulis).

DATA SOURCES
The report draws on two metadatabases of global household surveys—the Global Electrification Database managed
by the World Bank, and the Global Household Energy Database managed by WHO. Energy balance statistics andindicators for renewable energy and energy efficiency were prepared by IEA (Roberta Quadrelli, Francesco Mattion,
Faidon Papadimoulis) and UNSD (Leonardo Souza, Agnieszka Koscielniak and Costanza Giovannelli). The indicator oninternational financial flows to developing countries was prepared by IRENA (Adrian Whiteman, Gerardo Escamilla)
based on the IRENA Public Investments Database and OECD/DAC Creditor Reporting System. Data on gross domestic
product and value-added were mainly drawn from the World Development Indicators of the World Bank. Population
data are from the United Nations Population Division.

REVIEW AND CONSULTATION
The public consultation and peer review process was coordinated by the International Renewable Energy Agency(IRENA). Substantive comments were also provided by Donnee Alexander, Astri Sorenson, Dymphna van der Lans
(Clean Cookstoves Alliance), Elizabeth Cecelski, Sheila Oparaocha (ENERGIA), Sofja Giljova (GIZ), Rita Poppe (HIVOS),
Rana Adib, Thomas André, Duncan Gibb, Hannah E. Murdock, Lea Ranaldar (REN21), Glenn Pearce-Oroz (SEforALL),

CHAPTER 6 • Tracking SDG 7 progress across targets: indicators and data

195

Hongpeng Liu (UN-ESCAP), Rita Ruohonen (UN-OHRLLS). The IEA’s internal review process was led by Laura
Cozzi. The IRENA’s internal review process was led by Rabia Ferroukhi with contributions from Ahmed Abdel-Latif,
Elizabeth Press, Emma Åberg, Elisa Asmelash, Anindya Bhagirath, Emanuele Bianco, Gerardo Escamilla, Celia GarcíaBaños, Jinlei Feng, Ricardo Gorini, Carlos Guadarrama, Diala Hawila, Sandra Lozo, Gayathri Prakash, Michael Renner,
Costanza Strinati, Nicholas Wagner, Adrian Whiteman. UNSD’s internal review process was led by Leonardo Souza,with contributions from Agnieszka Koscielniak. The World Bank’s internal peer review process was led by Riccardo
Puliti, with contributions from Rohit Khanna, Rutu Dave, Zuzana Dobrotkova, Koffi Ekouevi, Stephen Halloway, Bryan
Koo, Ivan Jaques, Dana Rysankova, Inka Schomer, Xiaoping Wang and Yabei Zhang. The World Health Organization's
internal review process was led by Heather Adair-Rohani.

OUTREACH
The communications process was led by Emmanouela Markoglou and Daniella Van Leggelo Padilla (World Bank) incoordination with the custodian agencies’ communication focal points: Jethro Mullen and Merve Erdem (IEA), Nicole
Bockstaller and Nanda Febriani Moenandar (IRENA), and Nada Osseiran (WHO) and in coordination with UNSD. The
online platform (http://trackingSDG7.esmap.org) was developed by Advanced Software Systems, Inc. The report wasedited, designed, and typeset by Duina Reyes and Steven Kennedy.

196

Tracking SDG 7: The Energy Progress Report 2020

ABBREVIATIONS AND ACRONYMS
CO2

carbon dioxide

DRC

Democratic Republic of Congo

EJ

exajoule

ESMAP

Energy Sector Management Assistance ProgramGDP

gross domestic product

GHEM

Global Household Energy Model

GOGLA

Global Off-Grid Lighting Association

IEA

International Energy Agency

IRENAInternational Renewable Energy Agency

LEDlight-emitting diode

LPG

liquefied petroleum gas

MEPS

Minimum Energy Performance Standards

MJ

megajoule

MTF

Multi-Tier FrameworkMWhmegawatt-hourOECD

Organisation for Economic Co-operation and Development

pp

percentage point

PPP

purchasing power parity

PVphotovoltaic

REN21

Renewable Energy Policy Network for the 21st Century

RISE

Regulatory Indicators for Sustainable Energy

SDG

Sustainable Development Goal

SDS

Sustainable Development Scenario

SEforAll

Sustainable Energy for All

SHS

standalone home system

STEPSStated Policies Scenario

TFEC

total final energy consumption

TPES

total primary energy supplyTWhterawatt-hour

UNHCR

United Nations High Commissioner for Refugees

UNSD

United Nations Statistical Division

W

watt

WEM

World Energy Model

WEO

World Energy Outlook

WHO

World Health Organization

197

SDG 7 Technical Advisory Group

Funding
gratefully
acknowledged
fromUnited Nations
Statistics Division

Visit the SDG 7 Tracking website to download data and reports, as well as customized maps, comparativegraphics, timelines, and country reports.
http://trackingSDG7.esmap.org