Monthly Renewable Fuel and Hydrogen Survey (MRFHS)

Detailed information for January 2026

This survey collects information on the supply and demand of renewable fuels and hydrogen in Canada. This information serves as an important indicator of Canadian economic performance, is used by all levels of government in establishing informed policies in the energy area and, in the case of public utilities, is used by government agencies to fulfill their regulatory responsibilities. The private sector also uses this information in the corporate decision-making process.

Data release - To be determined

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

Description

This monthly survey covers the activities of all establishments in Canada engaged in the production and disposition of renewable biofuel. These data are required for integration into the Canadian System of National Accounts' input-output tables and for international reporting requirements. Under the authority of the Statistics Act, data are made available to other federal departments and provincial authorities through data sharing agreements that are subject to the embodied principles of data confidentiality. Data are also intended for use by survey respondents, industry associations, industry analysts and the general public.

Reference period: Month

Collection period: 10 days after the reference period.

Subjects

• Energy
• Energy consumption and disposition

Data sources and methodology

Target population

The survey is comprised of producers of the following fuels:
- ethanol,
- biodiesel (FAME),
- renewable diesel (HDRD/HVO),
- biocrude/bio-oil,
- alternative aviation fuel,
- other liquid renewable fuels,
- biogas,
- renewable natural gas,
- low carbon hydrogen,
- other gaseous renewable fuels,
- wood pellets.

The survey units are establishments.

Instrument design

Questionnaire Design Resource Centre (QDRC) testing was completed and approved.

The questionnaires were designed according to Statistics Canada's questionnaire design standards. They were designed in consultation with survey stakeholders, such as industry associations, government departments and key respondents. The questionnaire is completed by respondents in Excel format and delivered in electronic format.

The questionnaire will be subject to regular revision to reflect changes in business activities and practices.

Sampling

This survey is a census with a cross-sectional design.

Frame
A census using survey specific flags on the Business Register.

Sampling unit
The sampling unit is the establishment as defined in Statistics Canada's Business Register.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

The collection method is an Excel template in an electronic questionnaire shell. The initial method of contact is email, and follow-up will be done by phone or email. Both official languages will be offered as a choice to potential respondents. The average time to complete the interview and survey is less than 35 minutes. The survey unit is establishments.

Data from this survey will be combined with other energy statistics to create a consolidated energy report.

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

Error detection

Error detection is an integral part of both data collection and data processing. During data processing, edits are used to detect errors or inconsistencies that remain in the data following collection. These edits include value edits (e.g., value > 0 and value = 0), linear equality edits (e.g., Value 1 + Value 2 = total value), linear inequality edits (e.g., Value 1 = Value 2), and equivalency edits (e.g., Value 1 = Value 2). Extreme values are also flagged as outliers using methods based on the distribution of the collected information. After they are detected, these values are reviewed to assess their reliability. A manual review of other units may lead to additional outliers being identified. In general, every effort is made to minimize the non-sampling errors of omission, duplication, misclassification, reporting and processing.

Imputation

When non-response occurs, when a questionnaire is incomplete or when reported data are deemed incorrect during the error detection process, imputation is used to fill in any missing information and modify incorrect information. Many imputation methods can be used to complete a questionnaire, including manual changes made by an analyst. The statistical techniques used to impute the missing data include replacement using historical data, replacement using auxiliary information from other sources, and replacement based on known data relationships for the sample unit.

Estimation

All units in the observed population are being surveyed. The estimation of totals is done through a simple aggregation of the values of all estimation units found in the domain of estimation. Estimates are computed for several domains of interest, such as industrial groups and provinces and territories, based on the most recent classification information available for the estimation unit and survey reference period.

Quality evaluation

Prior to the data release, combined survey results are analyzed for comparability; in general, this includes a detailed review of individual responses (especially for the largest companies), general economic conditions, coherence with results from related economic indicators, historical trends, and information from other external sources (e.g. associations, trade publications, newspaper articles).

Disclosure control

By law, Statistics Canada is prohibited from releasing any information it collects that could identify any person, business or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. 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 the direct or residual disclosure of identifiable data.

Revisions and seasonal adjustment

Data are subject to revisions. Energy survey data and other supporting data are generally revised on a quarterly basis to reflect new information provided by respondents and updates to administrative data. Occasionally, there are exceptions when monthly revisions may be necessary, depending on the scale and impact of the revisions on the data series. Historical revisions will also be processed periodically.

There is no seasonal adjustment.

Data accuracy

The survey is a census of the target population. As a result, undercoverage is minimal, and minimal bias resulting from non-response is introduced. If changes are received from respondents, the data are incorporated and the published data are revised accordingly.