Statistics Netherlands

Energy department

Henri Faasdreef 312 | P.O. Box 24500 | 2490 HA The Hague

See table 3.1.1

See table 3.2.1

Energy statistics data covers all major sectors of the economy that are involved in the production, trade, energy transformation or energy consumption.

Definitions of Regulation (EC) No 1099/2008 on energy statistics apply.

See table under 3.5.1.

All bodies involved in production, transformation and consumption of energy.

The national territory, excluding the three islands in the Caribbean Sea which are special municipalities of the Netherlands.

See table under 3.8.1.

Not applicable.

See table under 4.1.

See table under 5.1

See below.

See table under 6.2.1.

Regulation (EC) No 223/2009 on European statistics (recitals 23-27, 31-32 and Articles 20-26) applies.

Confidential data are not shown. The most common approach is to present only aggregation of the confidential data point with the non-confidential data that is the nearest suitable data point.

The release calendar is publicly accesible.

Publicatieplanning (cbs.nl)

The CBS publication calendar lists the publication dates and times of all upcoming CBS news releases. All statistics are also published as tables in the StatLine databank and released at or after midnight (00:00 hours).

See table under 9.1.

See below.

All news release are published here: Energietransitie (cbs.nl)

All publications are published here: Energietransitie (cbs.nl).

Data is published on Statline: StatLine - Datasets by themes (cbs.nl)

Not requested for this metadata collection

Data on grid connections are made available through micradata services of Statistics Netherlands. 

Other disseminations are published here: Industrie en energie (cbs.nl).

Not requested for this metadata collection

CertiQ Registratie voor Garanties van Oorsprong van Hernieuwbare elektriciteit en warmte

Links to quality and methodology documentation (reference material on methods and questionnaires used):
https://www.cbs.nl/en-gb/our-services/methods/surveys/korte-onderzoeksbeschrijvingen/renewable-energy

Hernieuwbare Energie in Nederland 2020 (cbs.nl)

Protocol Monitoring Hernieuwbare Energie 2015 RVO CBS

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Survey on household wood use

Links to quality and methodology documentation (reference material on methods and questionnaires used):
WoonOnderzoek Nederland (WoON) (cbs.nl)

Hernieuwbare energie (cbs.nl)

Hernieuwbare Energie in Nederland 2020 (cbs.nl)

Houtverbruik huishoudens WoON-onderzoek 2018 (cbs.nl)

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

NEa register data on biofuels

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Renewable energy (cbs.nl)

Hernieuwbare Energie in Nederland 2020 (cbs.nl)

Link to national metadata:

See our See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Survey on sold wood boilers for heat >18 kW to enterprises

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Protocol Monitoring Hernieuwbare Energie 2015 RVO CBS

Hernieuwbare Energie in Nederland 2020 (cbs.nl)

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Production, transformation & consumption of energy

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Indigenous production, transformation and consumption of energy (cbs.nl)

Link to national metadata:

StatLine (cbs.nl) and StatLine (cbs.nl)

Crude oil and petroleum products

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Crude oil and petroleum products (cbs.nl)

Link to national metadata:

StatLine (cbs.nl) and StatLine (cbs.nl)

Energy consumption in Industry

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Energy consumption in industry (cbs.nl)

Link to national metadata:

StatLine (cbs.nl) and StatLine (cbs.nl)

Supply of electricity and natural gas via the national grid

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Supply of electricity and natural gas via the national grid (cbs.nl)

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Supply of natural gas

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Not available.

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Supply of electricity

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Not available.

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Production of oil

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Not available.

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Natural gas stocks

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Not available.

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

International trade statistics of goods

Links to quality and methodology documentation (reference material on methods and questionnaires used):

International trade in goods statistics (cbs.nl)

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

Production of biofuels

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Hernieuwbare Energie in Nederland 2020 (cbs.nl)

Link to national metadata:

See our StatLine database and tables on energy: StatLine (cbs.nl) and StatLine (cbs.nl)

CERES - register for energy systems

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Hernieuwbare Energie in Nederland 2020 (cbs.nl)

Protocol Monitoring Hernieuwbare Energie 2015 RVO CBS

Link to national metadata:

StatLine (cbs.nl) and StatLine (cbs.nl)

Disaggregated final energy consumption in households

Links to quality and methodology documentation (reference material on methods and questionnaires used):

Not available.

Link to national metadata:

Not available.

Not requested for this metadata collection

Internal procedures obligates us to document the statistical process in order to guarantee the quality of our output. Also we are reviewed and obtained an ISO 9001 certificate. Furthermore we document for each theme group (e.g. oil, electricity and heat, renewable) how data should be validated and before publication at least two experts have checked the data.

See also 10.7. Furthermore we developed software to compare outcome with previous calculated and published data to limited data errors.

In order to guarantee data quality we introduces digital boards where (possible) improvements are grouped and delegated. Furthemore we have an issuelist at our department to escalate (possible) risks in order to prevent them or solve as soon as possible. Weekly meetings per thematic group within our team also helps to increase data quality and transferability between team members.

Another important act to improve and guarantee data quality is to improve our tools for automatic processing data. Off course data resources are always checked by an expert. Before and after that most is done with software tools (or planned to be replaced by software tools) so that the process will be less sensitive to human mistakes, better repeatable and more efficient. Examples are our general software system in which for all sources that contribute to the Dutch energy balance similar data processing takes place (e.g. imputations, distract periods, balancing, aggregations) and also tools to help judge data (both survey data as well as registers).

As stated under 10.7 we have process documentation and we are reviewed yearly for ISO 9001 (review is internal every two years and external every two years). These reviews are thematic. Last external review was in 2022 and focused on the role of the manager and his grip on (possible) risks and how to guarantee data quality. The reviewer was very positive. This Fall there will be an internal review (theme unknown at the moment).

Classification of users:

• National ministries responsible for energy policy (Ministry of Economic Affairs and Climate (Overall coordination, energy supply and consumption in industry ), Ministry of Housing (residential and services sector), Ministry of Infrastructure and Transport (transport sector), ministry of Agriculture  (agricultural sector), ministry of Inland affairs (regional energy policy).
• Public and private research institutes providing advice/evaluation on energy policy to the ministries for national very often using our data as crucial element in compiling their reports (e.g. National Environmental Agency (PBL), National Energy Agency (RVO), Netherlands Organisation for applied scientific research (TNO), CE Delft)
• National Emission Registration (a national cooperation of several institutes responsible for official national greenhouse gas inventories)
• Eurostat and the International Energy Agency
• Regional governments
• Internal users of statistics Netherlands, like National Accounts and International Trade Statistics.
• Press, general public
• Actors on the energy markets, both suppliers and consumers.
• NGO’s
• Universities

It is difficult to put a hierarchy in the users, because often there also indirect relations. E.g. our data go the National Emission Registration and subsequently are used by NGO’s to sue the government for not achieving the target which leads to a lot of debate in parliament and newspapers.

 Use of statistical output

• Support energy policy at various spatial and time scales and various aspects
• EU, national, regional
• Annual, multi-annual, decades
• Evaluation (a.o. target accounting) and providing facts for forecasting/scenario studies
• Providing facts for well-informed public debate
• Support functioning energy markets
• Providing facts for taking informed decisions by actors on energy market

 Key outputs

• Energy balance. The balance by sector is tailored made to the needs of models of the national environmental agency.
• Joint annual energy questionnaires for Eurostat and IEA
• Monthly commodity balances at StatLine and for Eurostat and IEA
• (Micro)data for compiling for official national greenhouse gas inventories
• Regional data on electricity and natural gas consumption
• Contribution to national outlook on climate and energy
• Press releases

 Unmet user needs

• Of course users always want more timely, more detailed or more accurate date. However, there are budget constraints, there is a need to limit administrative burden for companies and citizens and there is limited access to data. Most users understand these limitations. In case users desire additional statistics they can always ask us to provide this if they provide sufficient resources, help to access to the relevant data and if the additional administrative burden is proportional. There is an important legal restriction regarding additionally financed activities of statistics Netherlands beyond the official statistical programme. We are not allowed to disturb the market for commercial statistical research, which implies that we are only allowed to do additional work if there is no private company who can do the same.
• In recent years we observed an increased interest in energy statistics. At EU level this materialized in intensive discussions in a task force of the Eurostat Working Group on Energy Statistics in which actively participated to discuss the new needs from policy at EU level and national levels. This resulted in a substantial expansion of the EU regulation on energy statistics mostly also responding to national needs. At national level we used these expansion of the regulation to successfully claim additional budget after which we started a process to hire new people to do the work.
• At national level we have several projects to expand our statistics to fulfill new demands.
• Last year we initiated the programme ViveT (Improvement of data for energy transition) together with several relevant stake holders. In this programme there was an intensive discussion with data uses and data suppliers to identify the real needs and most suitable data suppliers. This resulted in several new regional statistics, e.g. on regional renewable energy, data efficiency indicators in services (e.g. energy use per m2 for various types of buildings).
• We actively participate in the annual publication National Outlook on Climate and Energy as one of the co-authors. This publication is the main national annual report on energy and  climate covering the past and the future of the energy system as influenced by energy markets and national and international policy. By active participation there is direct connection to data needs for writing this report and the underlying models. Each year we have a (limited) budget for specific additional research tailored to the needs of this Outlook. We discuss with our partners the priorities.
• As a result of the demand from the national Parliament we started to publish quarterly data on greenhouse gas emissions about 2,5 months after the end of a quarter.
• In 2021 we had more than 40 publications (from simple tables to dashboards and  complete reports) outside the official statistical programme on dedicated demand from users: Industrie en energie (cbs.nl).
• During the Corona crisis there was a demand for more timely data on activities of the industry and in this respect we developed an indicator on weekly data of gas consumption by main industry subsector with one week delay (Indicatoren aardgasgebruik van de industrie (cbs.nl)). This indicator turns out to be even more useful in the current gas crisis.
• We wonder whether our annual publication on renewable energy still fulfilled user demand and would like to know their opinion on the trade of between timeliness and accuracy/level of detail. We have send out an e-mail to our contact list of 300 contacts to provide feedback. Several main users indicated that the publication was still useful and that preferred a later publication with detailed final data above a limited faster publication, in particular because main indicators are already released before summer via StatLine.

  Quality aspects of user needs

• A few years we had a correction of data on natural gas and refinery gas consumption in industry which substantially affected greenhouse gas emissions data. Major users like the emission registration and the environmental energy agency were not happy about this. We discovered this correction by comparing data on energy consumption from the ETS system at microlevel with our own data. To prevent the same errors in the future we try to incorporate comparison of data of energy intensive companies systematically with data of other sources, like the  ETS system, environmental reports and data from grid operators. For this purpose we formalized data delivery from the ETS system and we are  building tools to efficiently compare data.
• Eurostat pointed out in methodological paper that our reporting on blast furnaces was not in line with the reporting instructions.  We contacted the involved company and with the aid of the company changed the reporting, also backwards  to ensure consistency of time series (nationally back to 1990, internationally back to 2015, but we intend to revise internationally also back to 1990.
• For annual data of natural gas we still report transit flows, because of the complex physical gas system with a lot of storage, international connection, productions and a LNG terminal it is difficult to discriminate the transit flows and the large of part of the gas that is traded in an anonymous market. Nevertheless following discussion in the EWSG we intend to develop a method to make first order estimation of the transit. We have also had contact on the issue with the responsible Ministry and that are not are interested in a more accurate (and time consuming) approach, because they realize that is difficult to make this more accurate and because more accurate information on transit is not really needed for developing policy.
• Eurostat and IEA  published indicators on the dependency of several countries on Russian oil, gas and natural gas. We studied this indicators for usefulness in the Dutch situation and concluded that they were not suitable for use at member state level. Via e-mail and in meetings we explained to Eurostat our concerns.

We have no regular survey on user satisfaction. Annually we receive systematic feedback from IEA and Eurostat. For timeliness our score is mostly (very) good as for most quality aspects. We experience that for annual oil statistics improvement is possible according to IEA. This partly due to the very complex situation of the Dutch oil system with a lot of imports, exports, stocks, transit, refineries and petrochemical industry and the complex questionnaires of IEA and Eurostat not designed for the Dutch situation. This year we made more effort in coordinated response on the questions related to the annual oil questionnaire and we are curious to see the next report of IEA.

Despite having no systematic user survey we have intensive contact with several key users as also described in 12.1. This result in substantial expansion of our resources and statistical output. 

See below.

See table under 12.3.1.1.

A  lot of our statistical output is the result of multiple data sources. Accuracy analysis is therefore focused at the level of the statistical output and not of the individual data collections. The accuracy analysis of the output is described in chapter 13.  Data quality issues at the level of individual data collections is also described in chapter 18.

Every few years we make an overall analysis  of accuracy of main elements of the energy balance upon request of the Environmental Energy Agency (PBL)  or the National Emission Registration (which uses this as input for international reports on greenhouse gas emissions). Unfortunately, thus far we did not have time to make publication of this. In addition, in the annual report on renewable energy we annually publish an argued estimate of the accuracy for each renewable energy source (See Hernieuwbare Energie in Nederland 2020 (cbs.nl) for latest version, in Dutch).

The analyses of accuracy of the energy balance is based on taking into account several sources of errors and methods for estimating them.  These methods cover analysis of sampling errors, other errors, error propagation methods, statistical differences and comparison with other sources of information. Below a summary of this analysis.

For each main group of energy products we have one or a few crucial flows for which we analyze accuracy. The type of flow depends on the energy product, as not always the same flow is the most relevant.

Total supply and consumption of natural gas

For natural gas we have  independent statistical methods for supply and demand and the resulting statistical difference is therefore a reasonable indication of overall accuracy of production and consumption. For resulting statistical difference is about 2 percent max, which is considered reasonable according to the validation manual of Eurostat and also to our own opinion.  

Production and final consumption of electricity.

Also for electricity we have independent statistical methods for supply and demand and the resulting statistical difference is therefore a reasonable indication of overall accuracy of production and consumption. For resulting statistical difference is about 2 percent max, which is considered reasonable according to the validation manual of Eurosta, also to our own opinion.  

For electricity we observed last years a statistical difference which tends to be more negative every year which is a concern. Probably this due to inadequate observation of deliveries of electricity to the grid of small scale consumers (resulting in an over-estimate of final consumption of small scale consumers).  For electricity consumption of small scale consumers we use information from the grid operators. We know that due to the increased solar production of small scale consumers that they needed to changed their data collection methods and in 2021 we received for the first reporting year (2020) more complete data on the exchange of electricity of the grid for small scale consumers. Unfortunately, the quality of the data was still insufficient to be used for our purpose. This year we have received this more complete data for the second time and our first impression is that these data are suitable to be used.

Total consumption of primary coal products

Primary coals are used mainly in very limited number of plants: Tata steel complex (With a cokes-oven and blast furnace) and 4 coal fired power plants, which are subject of a monthly survey for several decades.  Experience learns us, there have been very little issues on total consumption which is confirmed by comparison with data of other sources (e.g. ETS) for the power plants.  We estimate overall uncertainty at about 1 percent, with 2 percent for the power plants and 2 percent for cokes-ovens/blast furnaces.

Production and consumption of secondary coal products

This covers coal gases an cokes oven cokes. Cokes oven cokes is produced and consumed by one company and tracking this straight forward. Coal gases are more difficult to trace because these gases are  mixed with each other and also with natural gas.  Coals gases are used by several parts of Tata steel and also delivered to neighboring power plants. Uncertainty on consumption of coal gases is about 10 percent, for overall coal products it is about 3 percent. We recently had a discussion with the involved company on the uncertainty of coal gases and they explained that also for themselves it is extremely difficult to improve on this.

Consumption of Crude oil and natural gas liquids (NGL)

Primary oil is used by refineries and petrochemistry, a limited number of plants subject to monthly survey, so sampling error is zero. Measurement of primary oil consumption is quite straight forward and there has never been any main issues in the past. We assume that accuracy is about 99 percent.

Oil products

Main oil products are gasoil, gasoline, heavy fuels oil, and kerosene. 

For gasoline inland deliveries is the most relevant flow. Data on this are based on a monthly survey for the major and medium suppliers, supplemented with indirect observation of smaller suppliers (via big companies that deliver to these smaller ones). Totals are annually compared with data collected in the framework of the obligation to use renewable energy in transport (closely to the tax system) and difference is about 1 percent.

For gasoil/diesel also inland deliveries is the most relevant flow. Data on supply  to the market are based on a monthly survey for the major and medium suppliers, supplemented with indirect observation of smaller suppliers (via big companies that deliver to these smaller ones). Totals are annually compared with data collected in the framework of the obligation to use renewable energy in transport (closely to the tax system, but with a slightly different scope and measurement unit (volume instead of mass) and difference is about 4 percent. Since about 10 years it is difficult to make accurately measure diesel for road transport since there is no separate tax tariff any more for diesel for road transport. Consequently, there is no need any more for oil companies to register to which sector they sell their fuels.  Recently, there has been some updated analysis on the use of gasoil/diesel in agriculture and construction and the recent update of the statistical regulation requires a break down of gasoil/diesel for transport. We intend to analyse all these issues together in cooperation with national partners within (transport statistics) and without our institute (Environmental agency, TNO). Currently the statistical difference of gasoil/diesel is about 4% of final consumption, which we believe is a reasonable estimate of accuracy.

Heavy fuel oil is mainly used for international marine bunkers. This flow is hard to measure, because of the numerous international operating companies involved. For example, it happens that ships in Rdam are supplied with bunker ships from Antwerp and possibly the other way around happens. Our method is based on following the flows from refineries, stock holding companies and main traders. We do plausibility checks with data from the port authority of Rotterdam. Based on the issues we encountered in recent years we estimate accuracy at about 90%.

Another main flow for oil is is non-energy consumption in (mainly) petchem industry, which is covered in a monthly survey to all relevant companies. So sampling error is zero.  Nevertheless petrochemical reporting is complex and sometimes we observe an error after analysis of ratio’s of input and output of petrochemical industry. Based on the issues we encountered in recent years we estimate accuracy at about 95%.

A limited number of companies is involved in buying fuels for Dutch airports. All these companies are part of a monthly survey. So sampling error is zero. Data are checked by main suppliers of kerosene. In recent years there have been no issues with these data. Therefore, we assume that accuracy is about 99.5%. 

Biomass consumption

Biomass is the main source of renewable energy. The most important source of uncertainty is caused by the share of renewables in municipal waste. This share is determined based on (a.o.) annual physical analysis of a  few hundred garbarge bags. Usually, a result of this analysis the share of renewable energy goes up or down one or two percentage points a year (3-4%). In the past we had an expert estimate of the uncertainty in the method of about 10%. The year-year variation is less, but the absolute level of accuracy is still unclear and therefore we stick to the estimate of 10% uncertainty. Another important source of uncertainty is in biomass consumption in households, even though this relatively small in the Netherlands compared to other countries.  We have a report (Houtverbruik huishoudens WoON-onderzoek 2018 (cbs.nl)) making estimates of uncertainty due to sampling, bias en measurement error and combining these errors resulting in overall estimated uncertainty of about 30% . Biomass in large scale applications like co-firing is much more accurate, because of the checks related to subsidies. We estimated overall uncertainty on total biomass consumption in 2018 at about 10%. In recent years growth of biomass consumption was concentrated in the relatively accurate co-firing. So, relative accuracy will have been improved in 2019 en 2020.

 Renewables other than biomass

For renewables other than biomass wind power is the most important. Almost all wind power plants are covered by the systems of Guarantees of Origin and there electricity production is measured accurately. We estimate relative uncertainty at about 2%.

We have access to the microdata of CertiQ, the body that manages the data related to the guarantees of origin. Solar electricity production is rapidly getting increasingly important. Until 2020 we estimate capacity from two main data sources (CertiQ far large systems) and Ceres for small systems. For the large systems the main challenge is two avoid any double counting if the systems appears twice in the database with a different ID and to tackle the systems that are already in the database, but not operational yet. For small systems registration is probably not complete. A few private studies from aerial inspection seems to indicate that 10-15 % of the small systems may be missing, though the quality of these studies is hard to verify by us. We estimate production with a  model calculation bases on radiation and the average production per unit of radiation and unit of capacity from Utrecht University from 2012. We intend to improve on this by using actual data for the large systems and an updated method for the small system. In the research for this we several compared the results from our existing method with other data sources and conclude that there is no indication that total solar production is far too high or too low. Overall estimated accuracy of solar production is about 15-20% covering both accuracy in capacity and accuracy in production per unit of capacity. Given the growing importance of solar PV we, and also national users, think this relative accuracy is too high. Therefore, we successfully asked for more resources to make these statistics and we will be able to invest more time on this from 2022 onwards.

Another important source of uncertainty is ambient heat captured by heat pumps. Capacity is calculated based on sales which is the default method we think. We check the population of selling companies with subsidy data and cooperation with the professional association. The main issue with ambient is the factors to go from capacity to captured ambient heat. These factors are to a large extent based on EU defaults, which are quite old and for which it is also not exactly clear what the empirical background is. Countries are encouraged to perform their own field studies.  At suitable accessions we try to generate interest for this at the national level, bit thusfar we are not very successful, because good, representative field work is costly.  For ambient heat we roughly estimate uncertainty at about 35%. 

We only use sampling for the Energy consumption in Industry survey. The sampling error for total final energy consumption for companies in scope of this survey is 1%. For publications based on NACE-category. sampling error varies between 0 and 28%, average sampling error is 7%.

Not requested for this metadata collection

Please refer to 13.1 for an extensive analysis on possible errors.

Please refer to 13.1 for an extensive analysis on possible errors.

See annex

See annex

See annex

Please refer to 13.1 for an extensive analysis on possible errors. Furthermore, repsponse rates are relatively high, so we do not expect the non response error to be large.

See annex

See annex

Please refer to 13.1 for an extensive analysis on possible errors. No significant examples are known of errors of this type.

Not applicable.

See below.

 See table under 14.1.3.

Not requested for this metadata collection.

Not requested for this metadata collection.

Most data deliveries are on time.

Not requested for this metadata collection.

All statistics are comparable between regions.

Not requested for this metadata collection.

There have been some changes but not enough to warrant the designation of a break in series

Not applicable.

We cross-check our statistics with statistics from other sources to make sure they are reconcilable.

We make sure that statistics of different frequencies are reconcilable.

National accounts uses our data as an important source.

We make sure statistics are coherent within a data set.

Costs

Cost associated to data collextion:

Cost associated to production of statistics is 17 FTE.

Burden

Burden on respondents is only known for two surveys. Burden is meassured in average time it takes respondents to fill in the questionaire.

Burden is minimised by keeping our questionaires as simple as possible. Furthermore, we use data from administrative source as much as possible, such that we do not have to contact companies.

We have revision policy which is not defined at the level of the data collection, but at the level of the published results, because that is what user experiences.

We publish provisional monthly data within 2 months after the reference period.
Provisional annual data are published as soon as sufficient reliable data are available, in the months February to June on the preceding year.
In November/December we publish adjusted provisional data which are consistent with the annual data that we submit to Eurostat/IEA and are also used for the Greenhouse Gas Calculations.
One year later we publish final results. Only for a limited number of items there is a difference between adjusted provisional and final.

Because we know that our users value consistent time series, we revise data whenever we find substantial improvements in our statistics.

Not requested for this metadata collection.

See below.

See table below.

See table under 18.2.1.

See table under 18.4.1.

See table under 18.5.2.

Not requested for this metadata collection

We do not apply seasonal adjustment.

An important adjustment we apply is the transposition of the data according to national definition for CHP heat production, input for CHP installation and final energy consumption to the international definitions. At national level derived heat includes usnsold CHP heat and all input of CHP installation is counted as transformation input. According to international definitions derived heat is restricted to sold heat and the part of the input of CHP installations that is allocated to unsold heat (based on the energy content of CHP output) is counted as final energy consumption. We apply this transposition at the lowest aggregation level for which the data are available and this part of the core of our IT system.

Another adjustment we make is the calculation of the some variables based on the assumption the statistical difference is zero for some products. This is the case in situations where it is difficult to arrive at reasonable data for both supply and demand. An example is solid biomass for which we have independent sources of information for consumptions, imports and exports, but not for domestic production. Domestic production is calculated from the other flows. It would be very difficult to compile independent statistics for domestic production, as there are many actors and markets are partly informal or do not exist.

For international trade we usually have quite accurate data on total imports or exports. Data for countries of origin and destination usually comes from the international trade statistics, with sometimes different definitions on e.g. transit. We adjust the data trade by country in such a way that it is consistent with total imports and exports.

We do not apply seasonal adjustments.