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CAT3525_C04.qxd  1/27/2005  11:12 AM  Page 103
                       Characterization of Solid Waste                                             103
                       EXCEL EXERCISE

                       WASTE CHARACTERIZATION
                       FILE NAME: CHARACTERIZ.XLS

                       Background
                       For this exercise, you will work with waste sampling data for the town of Goat Cheese, WI from
                       January 2001 through April 2002. The data are stored on a Microsoft Excel spreadsheet.
                          Waste is collected and the trucks are brought to the transfer station for unloading. Once a
                       month, a truck is randomly selected and dumps its contents on to a secluded portion of the tipping
                       room floor. Three university students were hired to sort the wastes into designated fractions and
                       then weigh the fractions.
                          At each sampling date, a subsample of this waste was fed into a micronizing mill (a small shred-
                       der) and the shredded mixture was weighed and combusted in a tabletop furnace. The ash was collected
                       and weighed. A separate subsample was shredded and placed in a bomb calorimeter. The heat content,
                       measured in BTU/lb, was determined.
                          The data for this exercise can be located at www.crcpress.com/e_products/downloads/
                       download.asp?cat_no=3525


                       Tasks
                         1. Calculate the percentages of each waste component for each month. What is the pre-
                             dominant fraction in the waste?
                         2. Determine the average values for each component over 2001.
                         3. Plot the data for total paper, plastics, food waste and yard waste, over the year 2001.
                             What trends do you observe?
                         4. Plot the data for BTU and ash content at each sampling date. Are any seasonal trends
                             observed?
                         5. Finally, perform a simple regression analysis of the heat content vs. ash content data. Is
                             there a significant correlation between the data sets? What is the correlation coefficient?
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