Methodology

a perfectible first version, but carefully developed

This is the first web interface in association with our "Co2manager" tool, which is able to compile data at the detailed level, to calculate configurable projections and to simulate the effects of emission reduction measures.
This interface (done in javascript, php, etc.) presents a serie of results of the Co2manager in a dashboard. The web interface and the Co2manager are at the stage of prototyping.

Data sources

All data is from sampling from two main data sources and some complementary sources:

The first database presents the whole spectrum of emissions. The second provides a greater level of detail, especially for three of the examined sectors: industry, electricity generation and hydrocarbon production. For the first version of the tool, three years have been selected in the periods 2004-2012, 2006, 2009 and 2012.

a first version of our synthetical review tool

The method used is inspired by "OLAP cubes", an IT tool used in decision-making. The method involves building a data set with a relatively detailed level of information that can be arranged according to the perspective of choice, according to several criteria of analysis:
  • sector/subsector/component if available (e.g. business/facility/type of vehicle)
  • CO2-equivalent emissions level/type of gas emitted,
  • Canada-wide/province/location
  • year.

Projections were made at detailed levels for 2020 and 2030. They were based on observation of trends with linear equations associated with threshold effects, and are adjustable.

Policy interventions are then simulated as interventions on projected data. The review tool contains a series of measures inspired by existing plans, studies and examples of regulations set elsewhere and configured for Canada. They are parameterized according to of several factors and assumptions.

maintenance of data

Data may shift and have to be regularly updated, such as:
  • integration of new emissions data,
  • integration of changes in emission counting modes (such as the value of the global warming potential of methane)
  • updating of the projection methods, depending on the progress of projects (cancelling of project, launch of new emitting projects...),
  • and... the establishment of new GHG reduction measures.

OLAP cubes

Working at the detailed level allows us to provide an accurate picture, even though each projected data set is approximate. The overall result is closer to reality than working with a larger scale, as in a raster image.

Next steps

We wish to develop our tool to make it more representative of your interests!
For example, an advantage of the method is to be able to combine several indicators, and that's what we want to do in a future release. We want and need your opinion!
We will soon publish a survey to assess the indicators that work for you.