Statistics Netherlands

• Environment Statistics

• Collect, process and publish waste statistics;
• Survey on municipal waste;
• Survey on non-hazardous waste generated by enterprises;
• Survey on public waste water treatment facilities;
• Survey on discarded vehicles;
• Statistics on waste from NACE G-Q, 37-39, 4677.

Rijkswaterstaat

• Waste Management Department

• Monitoring and formulation National Waste Management Plan;
• Statistics on hazardous waste;
• Statistics on construction and demolition waste;
• Statistics on Agricultural waste;
• Maintaining the national database of waste statistics.

Rijkswaterstaat

• LMA

• Host of the database with national waste transports in the Netherlands.

Rijkswaterstaat

• EVOA

• Writing permits and registration of transports that fall under the Waste Shipment Regulation.

IenW

• Dutch Ministry of infrastructure and Water management

• Responsible for national waste policy.

Kind-of-activity unit (KAU)

Fully compatible with WstatR requirements

T

T+1[year]

Municipal waste survey

Sending questionnaire

 Yes

Collecting questionnaires

 Yes

 Yes

 Yes

 Yes

 Yes

 Yes

 Yes

Data processing

 Yes

 Yes

 Yes

 Yes

 Yes

 Yes

 Yes

Manual check of the data

 Yes

 Yes

 Yes

 Yes

 Yes

 Yes

 Yes

Final data analysis and evaluation

 Yes

Data tabulation and publication

 Yes

Survey on waste generated by waste incinerators

Publication

 Yes

Secondary Waste

Determine sec. wastes in model

 Yes

Waste from NACE G-U, 37, 381, 382, 39, 4677

Linking database to business register

 Yes

 Yes

Extracting primary wastes

 Yes

 Yes

Determining non-response + data processing

 Yes

 Yes

Import, export, treatment of green listed wasteYes

Collecting International trade data (microlevel)

 Yes

Collecting waste transports to industry using AMICE

 Yes

Collecting imp/exp from AMICE register

 Yes

Integrating registers (avoiding double counting)

 Yes

 Yes

 Yes

Determining Treatment in the Netherlands

 Yes

 Yes

Waste Statistics Regulation

Collecting information and evaluation

 Yes

 Yes

 Yes

Publication

 Yes

 Yes

Legal basis of AMICE

The legal basis for reporting to the AMICE database is constantly changing. This implies that for some types of waste reporting or sectors can stop or start after a legal amendment. It is unclear how this affects data quality.

Reported waste categories

In the survey on manufacturing waste and waste from services, the introduction of new categories had an influence on the correction for the non-response. In general, the EWC-stat category 10.2 was mostly influenced and increased. In the food manufacturing industry, animal and vegetal wastes were affected. In paper industry, this affected paper and cardboard wastes and chemical wastes. For chemical industry, animal and vegetable wastes were affected, and in the metal industry, this was mainly mineral and chemical wastes. Also, some Eural codes of several companies were changed in the statistical process, to ensure that the waste was allocated to the right EWC-stat category.

Backfilling

For this WstatR we have defined backfilling as deposition of waste in mines. With this definition, there is no back-filling in theNetherlands. There is, however, export of wastes that are back filled elsewhere.

Comparability over time

• Due to a change of data sources, dredging spoils arisings are not comparable from 2006 to 2008. And from 2008 to 2010.
• Due to methodological changes, treatment data from the green listed wastes (EWC 06, 07 and 09) were not comparable from 2008 to 2010. We had hoped to streamline the method retrospectively later in 2012.
• Due to methodological changes, the method to estimate secondary wastes has changed in 2010 compared to 2008. This affects all waste arisings in NACE 38 and NACE 4677. This has been retrospectively adjusted for reference years.
• When we have finalized all the revisions, we hope to be able to do a delivery in Eural codes, as was asked by Eurostat.

The POM is back at its 'normal' level after a lower amount in 2020 due to the COVID pandemic.

• The administration and monitoring of all waste is formulated in the LAP 2017-2023 (National waste management plan) [1].
• Some companies are statutory required to publish an environmental performance report (e-PRTR) [2].
• Reporting entities are statutory required to deliver data to Statistics Netherlands [3].
• Transports of hazardous and non-hazardous waste are statutorily required to be registered for enterprises that have a provincial waste permit [4]. These registrations are the basis of the “AMICE”-database from NL Agency.
• Transboundary waste transports (except green-listed wastes) are statutorily required to be registered under the waste shipment regulation 259/93 [5]. These registrations are the basis of the “DaVinci” database from NL Agency.

 Due to changes in legislation and practice, the data sources are subject to changes.

Collect, process and publish waste statistics

Survey on municipal waste

Statistics on waste from NACE G-Q, 37-39, 4677

The generation of waste is calculated using a variety of methods and sources. Table 2 gives an overview of the sources and methods used to compile the generated waste. In brief this is:

Non-hazardous waste from NACE 01 to 03

Non-hazardous waste arisings from agriculture and fishing industries were determined by using a model, described at page 14, developed by Van Beusekom and Verbrockhaven [6]. Some parameters in the model were updated in 2008 data [7].

Non-hazardous waste from NACE 06 to 36 and 383

Data is collected using data published in the e-PRTR and supplemented with a sample survey. This is described in more detail at page 7.

Non-hazardous waste from NACE F

All waste arisings in NACE F, except dredging spoils, were determined using the registry of national waste transports (see page 13). For dredging spoils, registrations from the Rijkswaterstaat (ministry of infrastructure and environment) have been used.

Non-hazardous waste from NACE G-U (excl. 46.77), 4677, 37, 381, 382 and 39

The amount of generated non-hazardous waste is estimated by using the notifications in the AMICE database. This method is described in more detail at pages 10 to 13.

Non-hazardous waste from NACE 383

Non-hazardous waste arisings (excluding metallic wastes, combustion wastes and common slugde) were determined by a sample survey described at page 7. Common sludge waste arisings were obtained from a survey conducted by Statistics Netherlands. This survey is described at page 8.

Non-hazardous waste from Secondary wastes

Secondary wastes are obtained using treatment data of some waste streams. This is described in more detail at page 14.

Non-hazardous waste from NACE HH

A survey among all municipalities, described at page 7, is used to determine the waste arisings from households. Waste arisings of discarded equipment is obtained from the WEEE-Directive.

Table 2: Description of methods for determining waste generation

Table 5 shows the number of linked enterprises in comparison to the number of enterprises in the business register for NACE G-U. It appears that the number of enterprises in the non-response was considerable compared to the number of enterprises in the response. However, the response percentage increases if the enterprises become larger in size. Larger companies are generally expected to generate more waste. This will be beneficial for the accuracy of the statistics. This trend was similar for the other NACE categories (not shown).

For each 2 digit NACE, EWC-stat code, and size class, hereafter referred to as the cell, the following parameters were calculated from the response group.

• The amount of waste generated
• Total number of enterprises producing waste in general in 2digit NACE and size class for NACE G-U. The other NACE categories were divided into 46771, 46772, 46779, 381, 382, 37 and 39
• Number of enterprises producing the specific waste of the cell
• Median of waste generation
• Total number of enterprises in theNetherlands

Table 5       Coverage of the enterprises in the AMICE database to the business register

These results have to be interpreted with caution, as some cells can contain unrealistic information. An example of unrealistic data is that production waste is accounted to the financial holding, instead to the production facility. Another observation was that some cells were obvious double countings with waste from waste collection from municipalities. In those cases, all enterprises in the cell were transferred to the non-response. Obvious waste collectors in the NACE G-U, where also excluded from the response. These were:

• metal waste in NACE 46722 (Wholesale of metals and metal ores) and 46723 (Wholesale of wood, construction materials and sanitary equipment)
• Green wastes (EWC 09.13) from NACE 46216 (wholesale in raw vegetable and animal oil and fat and oil-containing raw materials)
• Waste in general from NACE 416 (Wholesale on a fee or contract basis).
• If the amount of waste exceeded 5000 kgper employee, the data was excluded from the data set for the wholesale of scrap and waste (4677) sector.
• If the amount of waste exceeded 10000 kgper employee, the data was excluded from the data set for the Freight transport by road and removal services (NACE 494)
• If the amount of waste exceeded 20000 kgper employee for EWC-stat group Metallic wastes (06), the data was excluded from the data set for NACE codes starting with 4.

For larger companies, another typical phenomenon occurs. It has been observed that not all local units of the kind-of-activity unit are linked to the business register. Waste occuring in these cells are notoriously under covered.

For those reasons, it is evident that statistics have to be made very carefully. Therefore, a suitable method had to be found to determine outliers, but not to delete real deviating data. This was done by calculating the average waste arising in the NACE G-U sector for a EWC-stat code and size class. A robust method appeared to determine the median of the waste arising per employee for each size class, EWC-stat combination. The calculated medians per employee were averaged for each EWC-stat code with excluding obvious outliers. Finally, the median per employee is used to calculate the median in the size class  (M_calc) by multiplying it with the average number of employees in the size-class. This M_calc­ represents the average waste arising for a size class for a EWC-stat code per enterprise, and was used to correct for non-response if the waste factors in the cell were unrealistic.

Then, an assumption is made how often the waste is expected to arise in the 2d NACE. This information is applied to determine the number of enterprises in the non-response group. Three waste patterns were distinguished. For common wastes, like household waste and paper waste, it has been assumed that the waste occurs in all enterprises. Thus, the business register has been taken as the population. Non-response was subsequently determined by subtracting the number of enterprises in the response (N_response) from the number of enterprises in the Netherlands (N­_{enterprises in NL}). The non-reponse was multiplied by the median, as seen in equation 1. The median of the cell (M­_cell), however, could display unrealistic data, as mentioned before. To prevent unrealistic extrapolations, the value of the M_cell has been compared to the median of the whole sector (M_calc). If M_cell deviated more than 2 times smaller/larger than M_calc­, the M_cell is rejected and M_calc is used to estimate for non-response.

W_non-resp = Median * (N_{enterprises in NL} – N­_{enterprises in response})                  (1)

For less common wastes, but still typical for the sector, we assumed that only a fraction of the companies produce the waste. This could be, for instance, rubber waste in wholesale and retail trade and repair of motor vehicles and motorcycles (NACE 45). The fraction that produces the waste has been chosen by a guess of ourselves of 10, 20, 30 or 50% of the enterprises. The other steps in the procedure were similar as described for equation 1. This leads to equation 2.

W_non-resp = (N_{enterprises in NL} – N­_{enterprises in response}) * Fraction * Median  (2)

The non-response was set to zero for incidental waste streams, such as metal waste in telecommunication (equation 3). Extrapolation for those wastes is expected to be unrealistic.

W_non-resp = 0                                                                                  (3)

Then the total waste arisings are calculated with equation 4.

W = W_non-resp + W_resp                                                                                            (4)

Treated waste = Generation of waste + Import – Export                                                         (5)

Several data sources were used to determine import and export amounts.

• For the orange and red-listed wastes, import and export were taken from the Waste Shipment Regulation [5].
• For green listed wastes imports and exports were obtained using the AMICE database and international trade. For a complete description how this has been done, see section on the import and export on green listed waste on pages 18 and 19.

Then, an average treatment of waste has been made for each Eural code. This has been done via empirical data of waste notifications and assumptions. This average treatment of waste was in line with the generated secondary wastes.

In practice three scenarios were calculated:

1. In case the waste is directly subjected to final treatment, the amount that is generated is simply added to the imports and exports are subtracted to determine the treatment of that waste (according to equation 5). The secondary wastes that arise during final treatment are added to the generation. Those secondary wastes are also accounted in the treatment table.
2. If wastes are subjected to pre-treatment, such as glass wastes, the secondary wastes that arise during sorting are added to the secondary wastes (metals, plastics, paper, and so on). The cleaned waste material (glass in the example) is not double counted. The secondary wastes are also accounted in the treatment table. The remaining glass that is final treated, is assumed to be recycled. Only, the impurities that were separated during pre-treatment are subtracted from the treatment (see equation 6).
3. Treatment of glass = Generation of glass waste – secondary wastes + imports – exports (6).

For some wastes, the waste is treated via various treatment channels. For instance, in some regions in the Netherlands, the household waste is directly incinerated (scenario 1). However, for other regions it is sorted (pre-treated) prior to final treatment (scenario 2). This is divided according to the previous scenarios.

The total amount of treated waste is researched independently by enquiring the disposal, incineration, and composting facilities in the Netherlands [10]. The outcomes of equation 6 are consistent with the value in that publication.

• Companies within category NACE 383 in the business register.
• Memberships of sector associations.
• Report from the study group waste treatment registration.
• Additional researches (e.g. internet).

Registry of waste treatment

Source              Waste Management Department

Treatment          All treatment methods

This registry contains data how each type of waste is treated on average. That is to say, waste item “a” is treated as: x % R1, y % R2, etc. For each waste item, the data is updated every 3 to 5 years. The information is gathered from several sources. Industry reports, transport notifications and assumptions.

      Treatment quantities of generated waste are determined by linking the registry of waste treatment to the generated waste from Annex I (see equation 5)

The numbers are corrected for the import and export to obtain the treated waste quantities in the nation (see equation 6). 

For metal, glass, paper and household waste, data on treated waste is obtained form sector associations or other sources. 

The total amount of composted, incinerated, disposed waste is taken from a report [10].

 Not applicable

• The EPR system performs cross-checks in waste management, year to year checks , and does audits ( at least 80 companies belonging to the top 250 of the country),
• The inspectorate is responsible for the audits and RWS does checks on general waste statistics and reports (for instance from housholds)

See above 18.4.4

 See above 18.4.4

See above 18.4.4

See above 18.4.4

See above 18.4.4

Packaging waste material

Description of measurement points used (at calculation point or at the output of sorting operation with subtraction of non-target materials as appropriate, end-of-waste criteria, etc.), including variation at regional and local level