We choosed to represent six end-use sectors for energy:
Non energy: energy commodities (refined pretroleum products, natural gas etc) embedded in material such as paints, varnishes, plastics, etc.
Personal Transport: includes personal vehicles, public transit, airplanes, etc.
Residential: includes lighting, heating, cooking, plugloads, etc. for where people live
Freight Transport: the movement of goods including by truck, train, ship, pipelines, etc.
Commercial and Institutional: includes lighting, heating and cooling in all commercial and institutional buildings (warehouses, stores, office buildings, universities, schools etc)
Industrial: the industry sectors that use (not produce) energy for manufacturing, mining, steel, cement, chemical industries, etc. In our energy Sankeys, the energy producing industry sectors are considered ‘service’ industries in the centre of the diagram that provide energy commodities such as refined petroleum production, pipelined natural gas, electricity etc. for the end use sectors.
Plot provincial or national primary energy use and associated greenhouse gas emissions for end-use sectors from 1978 to 2013, as total, per capita or per GDP.
I am wondering if you can offer any insights into the inter-provincial data for the personal transporation sector in Alberta. The end-use sector comparisons between provinces show that Alberta has the lowest energy/GDP & GHG/GDP & there is a difference in GHG/energy use in comparison to the other provinces. Alberta's overall energy use (PJ) and GHG emissions have been increasing in the personal transport sector since about 1991.
So the obvious explanation seems to be that the denominators are increasing. While that makes sense for GDP, I am trying to understand how this works for the energy use denominator. I am assuming this denominator is solely measuring energy use for personal transport.
Is there a numerator effect, such as newer (more efficient) vehicles in Alberta? Increased urbanization?
Or perhaps the denominator is measuring something that I am not picking up on?
The discrepancy you spotted regarding GHGs/energy use for personal transport was actually an error in the visualization tool we use to convert the CanESS model output into the graphs and figures. This has now been fixed so you can see that all provinces have similar values for GHG emission per energy use for personal transport (from 67.5 kt of CO2e per PJ in BC to 67.9 kt of CO2e per PJ in Saskatchewan in 2010). This reflects that all provinces relying on the same mix of technologies for personal transportation (i.e. internal combustion engines). Nevertheless, it's interesting to note that the overall emission intensity has decreased slightly since the late 1990's (-4.2% between 1997 and 2010).
In addition, your comment regarding the decreasing energy/GDP and GHG/GDP in Alberta is absolutely valid.
We really value feedback from users of this system. There are so many numbers and calculations behind these visualizations, that we cannot identify all the 'discrepancies' that exist without the sharp eyes and critical minds of our readers. Thank you.
Finding these mistakes is one reason we decided to post the output of the CanESS model and generate systems-level visualizations. Hopefully, with time we will track down all the problems and work to fix them. Thanks again for your contribution.
Comments
Brendan replied on Permalink
Energy/emissions efficiency of Alberta Personal Transport Sector
I am wondering if you can offer any insights into the inter-provincial data for the personal transporation sector in Alberta. The end-use sector comparisons between provinces show that Alberta has the lowest energy/GDP & GHG/GDP & there is a difference in GHG/energy use in comparison to the other provinces. Alberta's overall energy use (PJ) and GHG emissions have been increasing in the personal transport sector since about 1991.
So the obvious explanation seems to be that the denominators are increasing. While that makes sense for GDP, I am trying to understand how this works for the energy use denominator. I am assuming this denominator is solely measuring energy use for personal transport.
Is there a numerator effect, such as newer (more efficient) vehicles in Alberta? Increased urbanization?
Or perhaps the denominator is measuring something that I am not picking up on?
Thanks
Benjamin Israel replied on Permalink
Thank you for your useful feedback
Thank you very much, Brendan, for your comment.
The discrepancy you spotted regarding GHGs/energy use for personal transport was actually an error in the visualization tool we use to convert the CanESS model output into the graphs and figures. This has now been fixed so you can see that all provinces have similar values for GHG emission per energy use for personal transport (from 67.5 kt of CO2e per PJ in BC to 67.9 kt of CO2e per PJ in Saskatchewan in 2010). This reflects that all provinces relying on the same mix of technologies for personal transportation (i.e. internal combustion engines). Nevertheless, it's interesting to note that the overall emission intensity has decreased slightly since the late 1990's (-4.2% between 1997 and 2010).
In addition, your comment regarding the decreasing energy/GDP and GHG/GDP in Alberta is absolutely valid.
We really value feedback from users of this system. There are so many numbers and calculations behind these visualizations, that we cannot identify all the 'discrepancies' that exist without the sharp eyes and critical minds of our readers. Thank you.
Finding these mistakes is one reason we decided to post the output of the CanESS model and generate systems-level visualizations. Hopefully, with time we will track down all the problems and work to fix them. Thanks again for your contribution.