Script:
 What is in the analysis?
In starting the analysis of the green house gas emissions, also called GHG
emissions, of Washington University, several things were unclear at that time. This
aspect sprang out of that cloud. The comparison to other schools has many purposes at
its core. In this analytical section, the other school GHG emission inventories are
compared to better understand the Wash U data. The main purpose for this section is to
make sense of the data for Wash U, in a way. Mainly this serves to put everything into a
context. It is one thing to have the data; things take a new turn when one goes to analyze
it and make sense of it all. The reports of other schools contain information on emissions
from purchased electricity, stationary sources (things like cogeneration; laboratories;
steam plants; etc), transportation (university fleet; estimates on commuting students;
commuting faculty and staff estimates; and rarely air travel), agriculture wastes, and solid
wastes. Totals are also given as well as campus size and population of faculty/staff and
students. These are the different data that are compared here to see if any trends do exist
in the immediate future. Here on this slide, we see the extensive nature of the
survey/study. The exact number of schools survey is 31. This number will change with
time, as is expected.
 Why do this?
To help make sense of the inventory for WU, one needs to assemble a comparison
of all available colleges and universities. With the data now in a contextual framework,
the scope and magnitude of the emission is known. This is the first part to beginning the
planning of emission reductions. In addition to this, other schools do sometimes include
action plans which are helpful in brainstorming sessions, with thorough documentation.
Some of those ideas can be implemented at Wash U.
Another point to conducting a survey as it were of other schools is to examine
how others grappled with missing data for a given model. An example of this was
touched on by the transportation section of other school comparisons, earlier.
Also, this survey of the nation does tell Wash U what sources are important to
include and which ones are probably menial. As seen on this slide dealing with the
frequency of reported items. One clearly sees that purchased electricity, stationary
sources, transportation in its different forms and solid wastes comprise the minimal
basics of the total emission estimation. From this, the Wash U report can be structured to
include these. In addition to this, the effort here serves to validate the methodology used.
Do other colleges use the Clean Air-Cool Planet excel file or some other method? Most
colleges and universities do use this method devised by Tufts University, by a slim
margin which is growing in the recent years. Other methods implemented by schools for
the GHG inventory estimation include outside contractors and 1-2 yr studies by graduate
students in an environmental engineering major as well as a class project not unlike the
one in the EECE449-549 class which this is for.
 What does it show?
This shows that there is a general correlation between size and emission, not
applying the cliché. Here, it does apply. The correlation is a positive one in nature as is
visible from the graph. The bigger the college or university is in terms of total building
area, the more that place emits. This correlation is carried over in essence to the
population of the student body. The more students, the larger GHG emissions will be
made. This is logical in the confines of the causality model. Hence, the model does hold
here, WU is no exception. All of the colleges that report a total building area fall directly
on a curve of sorts. WU does as well. This can then be used to help WU plan out the
reductions and where to make them. Obviously, building efficiency will be considered, as
part of the reduction plan.
 What does this mean?
This serves as a benchmark of sorts to show where WU is now. It can be seen that
others are heading in the direction of more sustainable business practices from small
interim reports, where Wash U wants to head. By examining some of them, a data set for
given simple cheap strategies can be built. With this on the designing table, WU can
make plans and reduce emissions hopefully without too big of a cost hike. This avoidance
of cost hikes can help WU maintain its current style with an acceptance of the sustainable
ways. Thus, the community can shift more quickly to a sustainable style without too
much resistance. Wash U is seen as being in the middle of the chart on emission vs
campus size. As the rest of the national colleges begin to move toward this accord, Wash
U will need to change things to make that move. The curve in the diagram will begin to
shift downward as time progresses.
 Improvements
All things considered, improvements can be made by checking the data at hand
for errors in conversions. Often (regrettably) different schools will make the report for
greenhouse gas emissions in many different units. The most common is the metric ton or
tonne of equivalent carbon dioxide/yr (mTeCO2/yr), the unit used here in this report.
Others include short tons of carbon, short tons of carbon dioxide, and long tons of either
one. It would be of interest to chart the progress of the different schools for a number of
years based on the interim reports of GHG inventories. This would allow for the
observance of any trends with time and the available reduction plans. More comparison
trends can be made from the data, allowing for small studies to be done on one particular
aspect of the whole to see where the most logical place to make reductions. Such studies
will aid in planning out education/awareness campaigns to reduce the causality side of
the equation for emissions.
----End trans---Comparison methods
All of the above shows how this excel file was compiled. Though important, it is
not the sole item of concern. The methodology of comparison, however, is of major
concern here. For this, simple x-y scatter plots were done with the available data.
Typically this was done on the total GHG emissions in mTeCO2/yr. verse the school size
in terms of total square footage of the buildings. The scatter plot reveals logical results.
Another plot of total GHG vs. Student population reveals the same basic trends. There are
some odd points for this. These have been investigated and are deemed to be pseudooutliers.