OECD Environmental Performance Reviews
STATISTICAL ANNEXES 2019 DENMARK
OECD Environmental Performance Reviews: Statistical Annexes 2019 Denmark
This work is published by the OECD Environmental Performance and Information Division. The opinions expressed and arguments employed herein do not necessarily reflect the official views of OECD member countries. This document, as well as any data and any map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. This document presents statistical annexes which provide companion data to the Environmental Performance Review of Denmark published in 2019.
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
Photo credits: Cover Š Jezper/Shutterstock.com and Alexander Erdbeer/Shutterstock.com.
Š OECD 2019
Table of contents Figure 1.A1. Energy structure and intensity ........................................................................................... 1 Figure 1.A2. Road transport.................................................................................................................... 2 Figure 1.B1. GHG emissions and intensity............................................................................................. 3 Figure 1.B2. CO2 emissions and intensity .............................................................................................. 4 Figure 1.B3. SOx emissions and intensity ............................................................................................... 5 Figure 1.B4. NOx emissions and intensity .............................................................................................. 6 Figure 1.B5. PM2.5 emissions and intensity ............................................................................................ 7 Figure 1.C1 Waste generation and management..................................................................................... 8 Figure 1.C2. Material consumption and productivity ............................................................................. 9 Figure 1.C3. Agricultural impacts and livestock density ...................................................................... 10 Figure 1.D1. Fish catches and threatened species ................................................................................. 11 Figure 1.D2. Protected areas ................................................................................................................. 12 Figure 1.D3. Water abstraction and wastewater treatment ................................................................... 13 Figure 3.A1. Environmentally related tax revenue ............................................................................... 14 Figure 3.A2. Green growth innovation ................................................................................................. 15 Figure 3.A3. International development co-operation .......................................................................... 16
Figure 1.A1. Energy structure and intensity toe/USD 1 000
Energy supply per unit of GDP, 2017
0.37
0.25 0.20 0.15 0.10 0.05 0.00
Energy supply per capita, 2017
toe/capita
17.24
10 8 6 4 2 0
Energy supply by source, 2017 Coal, peat, oil shale
Oil
Natural gas
Nuclear
Renewables
Other
100% 80% 60% 40% 20% 0%
60% 50% 40% 30% 20% 10% 0%
88%
Share of renewables in primary energy supply, 2017
Share of renewables in electricity production, 2017 100% 80% 60% 40% 20% 0% Note: Data may include provisional figures and estimates. Total primary energy supply: the breakdown excludes electricity trade. GDP at 2010 prices and purchasing power parities. Source: IEA (2018), "World energy balances", IEA World Energy Statistics and Balances (database); OECD (2018), "Aggregate National Accounts, SNA 2008 (or SNA 1993): Gross domestic product", OECD National Accounts Statistics (database); UN 2018), World Population Prospects: The 2017 Revision (database).
1
Figure 1.A2. Road transport Motor vehicle ownership, 2016 Passenger cars
Other vehicles
Vehicles/1 000 inhabitants 1 000 750 500 250 0
Road vehicle stock, % change 2005-16 80% 70% 60% 50% 40% 30% 20% 10% 0%
n.a.
Consumption of road fuels, 2016 Diesel
Petrol
Biofuels
Other
100% 80% 60% 40% 20% 0%
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. Motor vehicle totals may not include exactly the same vehicle categories in different countries. Source: IEA (2018), "World energy balances", IEA World Energy Statistics and Balances (database); ITF (2018), "Transport performance indicators", ITF Transport Statistics (database).
2
Figure 1.B1. GHG emissions and intensity GHG emissions per unit of GDP, 2016 t CO2 eq/USD 1 000 0.6 0.5 0.4 0.3 0.2 0.1 0
GHG emissions per capita, 2016 t CO2 eq/capita 25 20 15 10 5 0
Change in total GHG emissions, 2005-16 60% 50% 40% 30% 20% 10% 0% -10% -20% -30% -40%
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. GHG emissions excluding emissions/removals from land use, land-use change and forestry (LULUCF). GDP at 2010 prices and purchasing power parities. Source: OECD (2018), "Air and climate: Greenhouse gas emissions by source", OECD Environment Statistics (database).
3
Figure 1.B2. CO2 emissions and intensity CO2 emissions per unit of GDP, 2016 t/USD 1 000 0.5 0.4 0.3 0.2 0.1 0.0
CO2 emissions per capita, 2016 t/capita 18 16 14 12 10 8 6 4 2 0
Change in total CO2 emissions, 2005-16 60% 50% 40% 30% 20% 10% 0% -10% -20% -30% -40%
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. CO2 emissions from energy use only; excluding international marine and aviation bunkers; sectoral approach. GDP at 2010 prices and purchasing power parities. Source: IEA (2018), "Detailed CO2 estimates", IEA CO2 Emissions from Fuel Combustion Statistics (database; OECD (2018), "Aggregate National Accounts, SNA 2008 (or SNA 1993): Gross domestic product", OECD National Accounts Statistics (database); UN 2018), World Population Prospects: The 2017 Revision (database). .
4
Figure 1.B3. SOx emissions and intensity SOx emissions per unit of GDP, 2016 kg/USD 1 000
2.2 3.4
1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 n.a.
kg/capita 40
SOx emissions per capita, 2016 102 155
30
20
10
0
n.a.
Change in total SOx emissions, 2005-16 40% 20% n.a.
0% -20% -40% -60% -80% -100%
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. GDP at 2010 prices and purchasing power parities. Source: OECD (2018), "Air and climate: Air emissions by source", OECD Environment Statistics (database).
5
Figure 1.B4. NOx emissions and intensity kg/USD 1 000 3.0
NOx emissions per unit of GDP, 2016
2.5 2.0 1.5 1.0 0.5 0.0
n.a.
NOx emissions per capita, 2016 kg/capita 120 100 80 60 40 20 0
n.a.
Change in total NOx emissions, 2005-16 60% 40% 20% n.a.
0% -20% -40% -60% -80%
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. GDP at 2010 prices and purchasing power parities. Source: OECD (2018), "Air and climate: Air emissions by source", OECD Environment Statistics (database).
6
Figure 1.B5. PM2.5 emissions and intensity PM2.5 emissions per capita, 2016 44
kg/capita 14 12 10 8 6 4 2
no data
0
Change in total PM2.5 emissions, 2005-16 40% 20% 0%
no data
-20% -40% -60% -80%
Average annual population exposure to air pollution (PM2.5), 2005 and 2017 2017
2005
µg/m3, average annual exposure levels of an average resident 50 45 40 35 30 25 20 15 10 5
n.a.
0
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. Population exposure to air pollution: estimates based on satellite observations and chemical transport models, calibrated against ground-based measurements using geographically weighted regressions. Source: OECD (2018), “Air and climate: Air emissions by source”, OECD Environment Statistics (database); OECD (2019), “Air quality and health: Exposure to PM2.5 fine particles - countries and regions”, OECD Environment Statistics (database).
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Figure 1.C1. Waste generation and management Municipal waste generation per capita, 2017
kg/capita 800 700 600 500 400 300 200 100
n.a.
0
Change in municipal waste generation per capita, 2005-17 50% 40% 30% 20% 10%
no data
0% -10% -20% -30%
Municipal waste management, by type of treatment, 2017 Landfill
Incineration without energy recovery
Incineration with energy recovery
Recycling and composting
Other treatment
100% 80% 60% 40% 20% n.a. 0% Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. Household and similar waste collected by or for municipalities, originating mainly from households and small businesses. Includes bulky waste and separate collection. CAN: data include construction and demolition waste. LVA: Data for "other treatment" refer to biodegradable waste recovery for biogas production. Source: OECD (2019), "Waste: Municipal waste", OECD Environment Statistics (database).
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Figure 1.C2. Material consumption and productivity DMC productivity, GDP per unit of DMC, 2017
USD/kg 5 4 3 2 1 0
Change in DMC productivity, 2005-17 150% 100% 50% 0% -50% -100%
DMC by material category, 2017 100%
Non-metallic minerals
Fossil energy carriers
Metals
Biomass
90% 80% 70% 60% 50% 40% 30% 20% 10% 0%
Note: Data refer to the indicated year or to the latest available year.They may include provisional figures and estimates. Domestic material consumption (DMC) equals the sum of domestic extraction of raw materials used by an economy and their physical trade balance (imports minus exports of raw materials and manufactured products). DMC productivity designates the amount of GDP generated per unit of materials used. GDP at 2010 prices and purchasing power parities. It should be born in mind that the data should be interpreted with caution and that the time series presented here may change in future as work on methodologies for Material Flow accounting progresses. Source: Eurostat (2018), Material flows and resource productivity (database); OECD (2018), "Material resources", OECD Environment Statistics (database).
9
Figure 1.C3. Agricultural inputs and livestock density
t/km2 agricultural land 16.0
Apparent consumption of nitrogenous fertilisers, 2016
14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0
t/km2 agricultural land 1.8
Pesticides sales, 2013-16
1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0
no data
Head of sheep eq./km2 agricultural land 3 000
Livestock density, 2016
2 500 2 000 1 500 1 000 500 0 Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. Conversion coefficients used to convert livestock heads in sheep equivalent: 1 for sheep and goats, 6 for cattle and buffaloes, 4.8 for equines,1 for pigs, and 0.06 for poultry birds. Source: FAO (2018), FAOSTAT (database).
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Figure 1.D1. Fish catches and threatened species Total fish catches per capita, 2017 kg/capita
Fish catches per capita
% change since 2005 (right axis)
200 3 536 477 150 100 50 0 -50 -100 -150 -200
100% 75% 50% 25% 0% -25% -50% -75% -100%
Threatened species as percentage of known species, mid-2000s Mammals All species Indigenous species 80% 60% 40% 20% 0%
n.a.
n.a.
Birds 80% 60% 40% 20% 0% Amphibians 80% 60% 40% 20% 0%
n.a.
n.a.
n.a.
n.a.
Vascular plants 80% 60% 40% 20%
n.a.
0%
Note: Fish data excludes aquaculture and excludes whales, seals and other aquatic mammals, aquatic plants and other miscellaneous aquatic animal products. IUCN categories critically endangered, endangered and vulnerable in % of known species. Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. Source: FAO (2018), FAOSTAT (database); OECD (2018), "Biodiversity: Threatened species", OECD Environment Statistics (database).
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Figure 1.D2. Protected areas Terrestrial protected areas, 2018 IUCN cat. I&II
IUCN cat. III&IV
IUCN cat. V&VI
No IUCN cat.
Areas reported as point
% of territory 60 50 40 30 20 10
n.a.
0
Marine protected areas, 2018 IUCN cat. I&II
IUCN cat. III&IV
IUCN cat. V&VI
No IUCN cat.
Areas reported as point
% of exclusive economic zone 50 45 40 35 30 25 20 15 10 5 0
95
n.a.
Note: Data include affiliated territories. Data for Australia exclude 2018 updates in the breakdown of marine protected areas (showing a shift from IUCN categories I-II towards categories V and IV). Data for Denmark include Greenland and Faroe Islands are currently under revision as regards the IUCN categorization of the areas protected according to the Danish Nature Conservation. Data for Turkey is not available, according to official sources about 9% of the territory is protected. Source: OECD (2018), "Biodiversity: Protected areas", OECD Environment Statistics (database).
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Figure 1.D3. Water abstraction and wastewater treatment m3/capita/year 1 800
Gross freshwater abstraction per capita, 2017 2 162
1 600 1 400 1 200 1 000 800 600 400 200 0
no data ..
Gross freshwater abstraction as percentage of renewable resources, 2017 50% 40% 30% 20% 10% no data
0%
Percentage of population connected to public wastewater treatment, 2017 Total public treatment (treatment level not known) Primary treatment only Other/not connected
Secondary and/or tertiary treatment Independent treatment
100%
partial data
80% 60% 40% 20% no data
0%
Note: Data refer to the indicated year or to the latest available year. They include provisional figures and estimates. Freshwater abstraction: for some countries, data refer to water permits and not to actual abstractions. Wastewater treatment: "other" includes connected without treatment, not connected or independent treatment (where there is no data for independent treatment). Source: OECD (2018), "Water: Freshwater Abstractions", OECD Environment Statistics (database); OECD (2018), "Water: Wastewater treatment", OECD Environment Statistics (database).
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Figure 3.A1. Environmentally related tax revenue Composition of environmentally related tax revenue by tax base, 2016a Energy
Motor vehicles
Other
Total % of total tax revenue
% of GDP 5%
% of total tax revenue 14% 12% 10% 8% 6% 4% 2% 0%
4% 3% 2% 1% 0%
Road fuel prices and taxes, 2017 Price excl. taxes
Excise tax
USD (PPP)/litre 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0
VAT
Unleaded petrol (RON 95)
n.a.
USD (PPP)/litre 4.0
Automotive diesel for non-commercial use
3.0 2.0 1.0 n.a.
0.0
Diesel (non-commercial use)
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. a) JPN: data for petrol refer to regular unleaded. Source: IEA (2019), IEA Energy Prices and Taxes Statistics (database); OECD (2019), "Environmental policy: Environmental policy instruments", OECD Environment Statistics (database); OECD (2018), Taxing Energy Use.
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ISL
USA
MEX
CAN
AUS
LUX
NZL
NOR
JPN
CHE
AUT
CHL
SWE
BEL
ESP
EST
IRL
ISR
FIN
FRA
GBR
LVA
DEU
HUN
KOR
POL
LTU
NLD
SVN
ITA
CZE
PRT
SVK
GRC
TUR
Tax rate (USD PPP/l) 2.00 1.75 1.50 1.25 1.00 0.75 0.50 0.25 0.00
Excise taxe rates on road fuelsa Unleaded petrol (RON 95)
Figure 3.A2. Green growth innovation
Environment-related R&D budgets, percentage of total government R&D budgets, 2017a 8% 6% 4% 2% 0%
Public RD&D budgets for renewables and energy efficiency, percentage of total public energy RD&D, 2017b Renewables
Energy efficiency
100% 80% 60% 40% 20%
no data
0%
Patent applications for environment-related technologies, percentage of all technologies, 2013-15c 20% 18% 16% 14% 12% 10% 8% 6% 4% 2% 0%
Patent applications for environment-related technologies, percentage of world total, 2013-15c 25% 20%
1.0% 0.8%
15%
0.5%
10%
0.3%
5%
0.0%
0%
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. a) Government budget appropriations or outlays for research and development (R&D); breakdown according to the NABS 2007 classification. b) Public energy technology budgets for research, development and demonstration (RD&D). c) Patents: higher value inventions that have sought patent protection in at least two jurisdictions (family size: two or more). Data are based on patent applications and refer to fractional counts of patents by inventor's country of residence and priority date. Source: IEA (2018), IEA Energy Technology RD&D Statistics (database); OECD (2018), Government budget appropriations or outlays for R&D (database); OECD (2019), "Patents in environment-related technologies: Technology development by inventor country", OECD Environment Statistics (database).
15
Figure 3.A3. International development co-operation Net ODA disbursements as percentage of gross national income, 2017 1.0% 0.8% 0.6% 0.4% 0.2% n.a.
0.0%
Bilateral ODA commitments to the environment, renewable energy and water sectors, average 2015-17a General environment protection
Renewable energy
Water supply and sanitation
% of total sector allocable ODA 30% 25% 20% 15% 10% 5% no data
0%
Bilateral ODA commitments targeting the environment, average 2015-17b Principal objective
Significant objective
Environmental ODA as % of bilateral allocable ODA
% of screened ODA 100% 90% 80% 70% 60% 50% 40% 30% 20% 10%
no data
0%
Note: Data refer to the indicated year or to the latest available year. They may include provisional figures and estimates. CHL, EST, ISR, LTU, LVA, MEX, and TUR are not members of the OECD Development Assistance Committee and report on a voluntary basis, thus data maybe not always be available, or may be partial. a) Renewable energy includes power generation/renewable sources; hydroelectric power plants; geothermal, solar, wind and ocean energy; biofuel-fired power plants. b) Data refer to aid activities designated with the environment policy marker (excluding those activities targeting the objectives of the Rio Conventions not marked for the environment). Activities are classified as “principal” when environment protection is a primary objective and “significant” when it is an important but secondary objective. In comparing data across countries it should be noted that the coverage ratio of the environmental policy objective (i.e. the proportion of aid which is screened against the environment policy marker) varies considerably among countries; low coverage rates can significantly increase the shares of environmentfocused aid. Source: OECD (2019), "Creditor Reporting System: Aid activities", OECD International Development Statistics (database).
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OECD Environmental Performance Reviews
STATISTICAL ANNEXES DENMARK 2019 This document presents companion data to the Environmental Performance Review of Denmark which was published in 2019.
2019