Chicago is a blue collar city. It doesn't matter how many iced mocha frappa water bottles you drink from the copious lexicon of chain coffee shops, outside smoking sections outside of overpriced overcrowded disco knock offs, or stacks of cars you fit into Fullerton on Sundays, the north side does not represent Chicago. Nor does the profuse putrid piles of pollutant particles come from the senseless waste of an unconscious, unaware critcal mass.
Chicago gets its pretty sunsets, smoggy overcast haze on a cloudless day, and rich black snow texture from the areas in town where there are no coffee shops, bars, or night clubs. There are seldom cars that course the streets where most of that fog thicket of greenhouse gaseous, poisonous and unproven cancer causing agents and intoxicating ether are manufactured. The blue collar of Chicago masks the electrical lymphnodes laden throat that swollows the bottle neck of commerse, traffic, consumption and breathes the smokey, charcoal flavored, blood aftertaste of gregariously jubilant exhale of societal exhaust. In short, it's where the factories and industrial sectors that built Chicago's economy during the spring of its blossom from anonymity that are responsible for the air quality in this city.
Locations detecting Carbon Monoxide
Once the areas where there was data for all three chemicals, I proceeded to chart out the valued information.
The task was to map out not only the spatial location of the concentric areas but also the year by year ratings and averages of the checmicals in question at each area. I decided to use a map of the CTA taped onto a cardboard box to represent the space. To represent time and different concentration values of the checmicals I stacked piles of differently colored sand into plastic bottles. The plastic bottles were chosen because they were clear and held a definite measurable dimension in the layers of sand and also because of the connotation of reusing recyclable materials. For every unique annual value of a checmical in an area, there was a new layer of sand added to represent it. A timeline was then drawn connecting data points all around the bottle. One bottle represents all of one checmical's reading per location. Cutouts in the diameter of each bottle were then cut out clustering around the overlapping area where the chemicals were detected in Chicago on the CTA map. The bottles are distinguishable as the chemicals they represent by the scents associated with them.
The bottles are intended to be picked up and examined, smelled, observed and replaced one by one so that they are not confused with bottles of another area.
While the values represented on the bottles by sand layer division are relative to the breadth of chemical level. per area, it can be seen by the numerical correlative to individual points drawn on the bottle that higher values of each chemical group were found on the south side industrial area versus the lake front and the near north side locations. A lesson that can be learned from this method of representing degrees of variance is to not make the quantity of sand in each bottle subjective, but use it to reflect an actual real world value. If I were to do this project again, I would use real world values on the bottles measured to the same distance on every bottle (ie 1ppm = 1in or something like that). Then divisions in layers of sand would be meausered out to the objective scale metric. All the data needed to do comparissons are present, but the results would be much more quantifiable and visually comparable if the amount of sand in each bottle was measured out. The emphasis of this project as more on the variability of chemical readings per year per location in Chicago. However, the most interesting point of the compilation of data is most certainly the levels of pollutants in different areas of Chicago.
