THE PROBLEM
The total air miles traveled by the world's commercial airliners
are tiny compared with the humble but ubiquitous terrestrial motor
vehicle. Approximately 72 Mt of nitrogen oxides (NOx as NO2) are
produced by man-made sources at the Earth’s surface, globally,
while an estimated 2.8 million tons of NOx are produced by aircraft
from the surface up to approximately 17km.
Observers may consider the pollution produced
by air traffic to be too insignificant to worry about, except for
one factor. Emissions of nitrogen oxides close to the top of the
troposphere are shown to have a “radiative forcing” effect
on surface temperatures of about thirty times that of surface emissions,
and suddenly, the effect of those aircraft has significance.
In 1994, Dr. Lee was assigned the problem
of examining the three-dimensional distribution of aircraft emissions
in the atmosphere. These data came from a large collaborative European
project, the ANCAT emissions inventory. "From the start of
the project we realized we would be dealing with a large amount
of data, including geographic information," said Dr. Lee, "
so we knew we would need a software tool capable of reading multiple
formats and of combining to a single image."
The completion of the ANCAT inventory was
daunting. First, other partners of the group compiled the flight
paths of every jet aircraft worldwide, including scheduled and charter
flights and smaller private jets that fly the same airspace as commercial
aircraft. Second, in order to establish the quantities of emissions
along every flight path, data on climb and cruise emissions for
each jet type were calculated. For example, an aircraft climbing
out from its departure airport uses many times more fuel per km
than one cruising at high altitude.
The
German Research Institute for Air and Space Travel provided a simulated
model for each aircraft type. "Much of the data we used were
available, albeit in a rich variety of formats," commented
Dr. Lee. "It simply required a huge amount of standardizing
and combining. Data verification, however, can be more difficult."
Finally, the data were passed on to AEA Technology in the form of
a 3D coordinate detailing final fuel usage and calculated NOx emissions.
THE SOLUTION
The next task was to multiply the flight paths by the emissions
models for each aircraft type. The result was twelve arrays of data,
one for each 1,000 m above sea level. Each is based on a 2.80 x
2.80 grid (a total of 147,456 data points to cover the earth, up
to 17 km in the atmosphere). "Other members of the group had
modeled fuel usage and NOx emissions; now we needed PV-WAVE to see
the results," said Dr. Lee. "That's where the software
came into its own."
The system can open and display any data set, given a few descriptors.
With his first experiments, Dr. Lee could read each of the data
files in turn and see the emissions at each level of the troposphere.
The world map provided with the software allows the picture to be
superimposed on a globe. By using PV-WAVE’s color tables, areas
of differing emissions can be shown as a “heat map.”
Taking the analysis further, Dr. Lee developed a simple PV-WAVE
routine to load all the data sets simultaneously and display them
on the Earth’s surface. Further routine calls allowed Dr. Lee
to “slice through” a longitudinal cross section. “The
results of this graphical analysis highlighted the imbalance of
emissions in the Northern Hemisphere, for example," commented
Dr. Lee.
RETURN
ON INVESTMENT
The ability to interact with the data allowed Dr. Lee to pinpoint
features in the data. “We found we had a few lines appearing
at the highest level, close to the tropopause — the band between
the troposphere and the stratosphere. Much of these emissions can
be explained by Concorde flight paths — following ‘the
great circle route’ to the USA and Rio de Janeiro. One of the
great benefits of PV-WAVE is its flexibility,” concluded Dr.
Lee. “I can use it to interact with the data, view it in different
ways, try different color tables and cross sections through the
information to identify trends and patterns. The end result is that
we can visually analyze our data, pick up on the features and present
them to environment researchers who will be working with our output.”
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