Thank you again for inviting us here.
The point we want to make about the current state and future of national energy data is obviously in relation to our modelling activities, which are our core activities. Models, in fact, are great tools to support policy-making, but they are very necessary when it comes time to analyze very complex issues, such as managing major energy transitions to reduce greenhouse gas emissions without compromising economic growth and taking into account social preferences.
Energy system models, in particular, are more important for many reasons. The two most important ones are, first, to understand the magnitude of the problem, which is not necessarily obvious to the public in general nor even the government officials we are working with. The second thing is to explore and identify the most cost-effective pathways that would allow us to achieve ambitious greenhouse gas emission reduction targets, like the one Canada has proposed for 2050, and reach a low-carbon economy, which would be healthy.
All over the world, the results coming from these models are increasingly used to inform policy-makers, but also industries and any organization or individual who could be impacted by a change in the energy supply-and-demand dynamics, by energy prices, or by greenhouse gas emissions and their impact. Actually, the specific categories of models we are using right now are used in more than 70 countries around the world already, for both energy and climate policy analysis. However, the relevance and usefulness of these models are strongly dependent on the input data to start with. This is why it's very important and quite urgent—according to us—that Canada puts in place a program or an organization, or whatever entity, that would ensure good access to good quality data that are consistent and comprehensive for the needs we have, so that we can better help with policy-making and make the public understand the issues regarding climate change and the magnitude of the problem to solve.
In our brief, we have listed some of the most important gaps we have faced during the TEF project, and also different projects. We have been doing this kind of analysis for 15 years now. The intention here is not to repeat all of them—there's the brief for that.
Basically, gaps are more or less everywhere in all the dimensions of the data we need, including our very first starting point, which is the energy balances provided by Statistics Canada—the report is called “Report on Energy Supply and Demand in Canada”—which exist for the 13 provinces and territories. They are incomplete. They do not capture the emerging energies like biofuels or wind energy, and so on. There are many Xs all over the place, especially at the provincial level. At the aggregated level for Canada it's not too bad, but at the provincial level it's very difficult, especially in the industrial sector, and especially regarding the refined petroleum product production, trade, and so on. It almost doesn't exist anymore in the Atlantic provinces, or even in the western provinces.
The report data are not supported by more detailed and reliable statistics on the technology stocks that are behind the data on energy consumption. The office of energy efficiency, for instance, provides more detail on energy used by subsector and so on, but the technology stocks and so on comes from a survey that we know doesn't cover the full sector, so we are never sure if we can rely on these statistics or not.
We need the full bunch of data regarding the technical and economic attributes of technology that we put in our models.
The Canadian models we are running right now show 5,000 technologies used in each region, in each province in technology, so we have to look at these specific parameters one by one within a large diversity of sources, including reports, scientific papers, Ph.D. theses, websites of retailers, and even physical visits to retailers. I don't know how many times I've gone to Reno-Depot looking for specs of a new technology, the cost of the best-selling furnace for an apartment, and so on. It's a huge job to be able to compile a database for these models even in an ideal world, because these models are very much data-driven and this is very time-consuming.
Right now, in situations where the data are difficult to access, we spend a lot of time looking for data, trying to reconcile conflicting information, trying to fill the gap with our own assumptions, trying to validate these assumptions with experts in the field, and so on. Having access to better data would allow us to spend more time developing the model itself and implementing fancy stuff like smart grid and smart buildings, things that we don't necessarily have the time to do because we are updating our database. We could spend more time studying the problem and trying to provide some pieces of the solution.
Having said that, we have been quite successful in building a good database for Canada, but it required an intense effort for more than 10 years through consulting and research projects. That's why we can use the model today for policy analysis, but this work never finishes because every year we have to update the data and the energy balances, and we have to update the database each time a new technology comes on the market. For example, there was a big announcement recently on this new technology to make aluminum without process emissions. We are just looking forward to integrating that into our models, but we currently don't have data for that.
The last point we would like to make, which is not in our brief, is that we think that, along with the necessity of having an organization that would ensure better access to data and better quality data, we need to make the collaboration between data providers and data users stronger, because right now it's a bit difficult. We send emails and we write to data providers like StatsCan, in particular. Sometimes we don't even get an answer, or sometimes we get an answer, but three weeks later, with a copy-paste of a footnote of a table that is already in the report and that we have already read 10 times.
This is a bit difficult, when we try to know more about what is behind particular data, so a stronger collaboration would be better for us to better understand the data and how to use them, but it would also be better for the government, because then you know more about our needs and it's easier to set up the priorities, because obviously we would not be the only ones who will use this data. Many people are looking to have something similar to what we are suggesting.
I don't know if you want to add something.