Biennial Waste Management Survey

Detailed information for 2022

This survey collects information that will help Canadians understand the contributions the waste management industry makes to Canada's economy and environment.

Data release - April 8, 2024 (Waste diversion); July 2, 2024 (Waste disposal)

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

The survey provides comprehensive information about waste generated by Canadians, waste disposed and diverted from landfills, and their sources. This information is collected from businesses that provide waste management services, and from retailers and other organizations that participate in diversion programs outside of the waste management stream.

These data are used by local governments, Environment Canada and various other public and private clients.

Reference period: Fiscal year

Collection period: Spring and summer following the reference year

Subjects

• Environment
• Pollution and waste

Data sources and methodology

Target population

IN-SCOPE WASTE MANAGEMENT BUSINESSES SECTOR
The target population includes all firms operating in Canada that provide waste management services.

The survey frame is based on information from the previous survey, supplemented and updated with information from the Statistics Canada Business Register (BR) and industry directories. Firms selected from the BR are a subset of Waste management and remediation services, North American Industry Classification System (NAICS) 562.

The following NAICS classifications are considered to be "in scope" for the Waste Management Industry Survey: Business Sector: 56211, Waste collection; 56221, Waste treatment and disposal; and 56292, Material recovery facilities.

IN-SCOPE LOCAL GOVERNMENTS THAT PROVIDE OR MAKE PROVISION FOR WASTE MANAGEMENT SERVICES
The target population for this survey of waste management practices includes all large municipalities (population of 5,000 or more), or waste management commissions or boards representing municipalities.

IN-SCOPE RETAILERS AND OTHER ORGANIZATIONS THAT PARTICIPATE IN DIVERSION PROGRAMS OUTSIDE THE WASTE MANAGEMENT STREAM
The following NAICS classifications are considered to be "in scope".

4142, Home entertainment equipment and household appliance merchant wholesalers; 4181, Recyclable material merchant wholesalers; 4182, Paper, paper product and disposable plastic product merchant wholesalers; 449 Furniture, home furnishings, electronics and appliances retailers; 445, Food and beverage retailers; 455, Department stores.

• Additional documentation

Instrument design

The majority of the questions remain unchanged from cycle to cycle. In 2020, questions were added to capture specific information related to non-traditional waste management streams. In 2022, more questions were added to diversify plastics to better understand the flows of plastics from generation through to final disposition.

Sampling

IN-SCOPE WASTE MANAGEMENT BUSINESSES SECTOR
This is a census with a revenue cut-off.

IN-SCOPE LOCAL GOVERNMENTS THAT PROVIDE OR MAKE PROVISION FOR WASTE MANAGEMENT SERVICES
This is a census with a population cut-off.

IN-SCOPE RETAILERS AND OTHER ORGANIZATIONS THAT PARTICIPATE IN DIVERSION PROGRAMS OUTSIDE THE WASTE MANAGEMENT STREAM
A sample is selected from this portion of the target population.

The Generic Survey Universe File is used to extract the survey frame.

A stratified sample of establishments classified at different North American Industry Classification System (NAICS) Canada 2022 levels and to geographical regions is selected. Respondents from reference year 2020 who are in-scope and a list of establishments provided by subject matter are selected with certainty.

Data sources

Data collection for this reference period: 2023-03-15 to 2023-09-23

Responding to this survey is mandatory.

Data are collected directly from survey respondents and derived from other Statistics Canada surveys.

Data are collected directly from survey respondents and alternate data sources.

Data are collected using an electronic questionnaire. Respondents are emailed invitation letters and Secure Access Code letters. A letter explaining the purpose of the survey, the requested return date and the legal requirements of response are included as a package in the email invitation.

Follow-up procedures are applied when a questionnaire has not been received after a pre-specified period of time. Note that the questionnaire is available in both English and French versions.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Many factors affect the accuracy of data produced in a survey. For example, respondents may have made errors in interpreting questions, answers may have been incorrectly entered on the questionnaires, and errors may have been introduced during the data capture or tabulation process. Every effort is made to reduce the occurrence of such errors in the survey. These efforts included: a complete verification of keyed data, validity and consistency edits, extensive follow-up with the large businesses, and consultation with selected government departments and industry associations.

Imputation

Although most businesses and local governments cooperate in answering the survey, some cannot provide all the data required in the form in which they are requested. In cases where values are missing from survey cells or where the respondent did not complete a questionnaire even after extensive follow-up, information is imputed.

IN-SCOPE WASTE MANAGEMENT BUSINESSES SECTOR, AND
IN-SCOPE LOCAL GOVERNMENTS THAT PROVIDE OR MAKE PROVISION FOR WASTE MANAGEMENT SERVICES
For larger firms and local governments, the imputed values are compared with values from previous years and other sources, such as annual reports and filings with the provincial authorities for local governments, to ensure that the high quality of imputed values.

IN-SCOPE RETAILERS AND OTHER ORGANIZATIONS THAT PARTICIPATE IN DIVERSION PROGRAMS OUTSIDE THE WASTE MANAGEMENT STREAM
Different statistical imputation methods are used for total non-response and partial non-response records. Three methods of imputation are used:
- deterministic imputation (there is only one possible value for the field to impute);
- imputation by mean;
- donor imputation (using a nearest neighbour approach to find, for each record requiring imputation, the valid record that is most similar to it);
- manual imputation.

The criteria used for mean and donor imputation are various combinations of industry group, and geographical location (province, region, or Canada). Statistics Canada's generalized edit and imputation system (Banff) is used for this process. Usually, key variables are imputed first and are used as anchors in subsequent steps to impute other related variables.

Imputation generates a complete and coherent microdata file that covers all survey variables.

Estimation

This methodology is used for the retailers and other organizations module. It is not applied to the local government and business sectors.

The Generalized Estimation System developed at Statistics Canada is used to produce domain estimates and quality indicators. It is a SAS-based application for producing area-level estimates for a population based on a sample.

An initial sampling weight (the design weight) is calculated for each unit in the survey and is the inverse of the probability of selection. The weight calculated for each sampling unit indicates how many other units it represents. Sampling units that are selected with certainty (must-take units) have sampling weights of one and represent only themselves. Outlier units with larger than expected sizes are considered misclassified and their weights are usually adjusted to represent only themselves. The weights of other units are adjusted accordingly to account for the existence of outliers. The final weights are usually either one or greater than one. Sampling error is measured by the coefficient of variation (CV), which represents the proportion of the estimate that comes from its associated variability. CVs are calculated and are indicated in the data tables.

Quality evaluation

One way to assess data accuracy is to compare it with data from other sources. For example, if the survey data indicate that the amount of waste disposed and diverted has risen substantially since the previous survey, operating revenues and expenses can also be expected to have risen. Similarly, if a provincial report is released indicating that the amount of diverted materials has increased significantly in that province, the data obtained from these surveys can be expected to follow the same trend. If the data do not follow the expected trends, they are investigated rigorously.

In addition, data are compared with those published by other organizations, such as provincial governments and cities. If there are significant differences between the different sets of comparable data, these must be accounted for and explained. This also applies to cases where there are large positive or negative changes in the data values from cycle to cycle.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects under the Statistics Act that could identify any person, business or organization, unless written consent of that person, business or organization has been given. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

An intensive peer review of all tabular data is conducted prior to publication. This manual verification ensures that both inter- and intra-tabular comparisons cannot be made that may lead to disclosure of confidential data.

Revisions and seasonal adjustment

Revisions are made for the previous survey reference period with the initial release of the current data, as required. The purpose is to address any significant issues with the data that were found between survey cycles. The actual period of revision depends on the nature of the issue, but rarely exceeds four years, or two survey cycles. For the most current data, please refer to tables 38-10-0032, and 38-10-0138.

Data accuracy

The accuracy of data collected in a survey is affected by sampling and non-sampling errors. Sampling errors arise from the fact that the information obtained from a sample of the population is applied to the entire population. The sampling method as well as the estimation method, the sample size and the variability associated to each measured variable determine the sampling error. A possible measure of sampling error is the coefficient of variation (CV). It represents the proportion of the estimate that comes from the variability associated to it.

Non-sampling error could arise from coverage error, data response error, non-response error and processing errors. Every effort is made to reduce these types of errors, including careful questionnaire design, verification of keyed data, consistency and validity edits, and extensive follow-up and consultation with government departments and industry associations.