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TABLE 15.6 SIC CODE GROUPS THAT COMPRISE THE 22 SELECTED WASTE GROUPS (CLUSTERS) (CONTINUED) WASTE GROUP NAME (CLUSTERS) SIC GROUP NUMBER
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NUMBER OF COMPANIES
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Legal services Social services Membership organizations Engineering, accounting, research, management, and related services Executive, legislative, and general government, except nance Justice, public order, and safety Public nance, taxation, and monetary policy Administration of human resource programs Administration of environmental quality and housing programs Administration of economic programs National security and international affairs Building construction general contractors and operative builders Heavy construction other than building construction contractors Construction special trade contractors Educational services Industrial and commercial machinery and computer equipment Electronic and other electrical equipment and components, except computer equipment
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17 6 7 Education (EDU) Electronic manufacturers (ELM) 82 35
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(Continued )
SUMMARY OF WASTE CHARACTERIZATION FINDINGS
TABLE 15.6 SIC CODE GROUPS THAT COMPRISE THE 22 SELECTED WASTE GROUPS (CLUSTERS) (CONTINUED) WASTE GROUP NAME (CLUSTERS) SIC GROUP NUMBER
DESCRIPTION
NUMBER OF COMPANIES
Measuring, analyzing, and controlling instruments; photographic, medical and optical goods; watches and clocks Miscellaneous manufacturing industries Food and kindred products Food Stores Forestry Hotels, rooming houses, camps, and other lodging places Health services Primary metal industries Fabricated metal products, except machinery and transportation equipment Metal mining Coal mining Motor freight transportation and warehousing Paper and allied products Printing, publishing, and allied industries Motion Pictures Amusement and recreation services Museums, art galleries, and botanical and zoological gardens
39 8 9 10 11 12 13 Food manufacturers (FDM) Food stores (FDM) Forestry (FOR) Hotels (HTL) Medical services (MED) Metal manufacturers (MLM) 20 54 08 70 80 33 34
7 8 9 3 7 14 4 6
Mining (MIN)
10 12
3 3 5 6 8 6 4 4
(Continued )
15 16
Motor freight and warehousing (WAR) Paper manufacturers and printers (PPM)
42 26 27
Recreation and museums (REC)
78 79 84
SOLID WASTE CHARACTERIZATION BY BUSINESS ACTIVITIES
TABLE 15.6 SIC CODE GROUPS THAT COMPRISE THE 22 SELECTED WASTE GROUPS (CLUSTERS) (CONTINUED) WASTE GROUP NAME (CLUSTERS) SIC GROUP NUMBER
DESCRIPTION
NUMBER OF COMPANIES
18 19
Restaurants Retail and wholesale trade (RTL)
58 50
Eating and drinking places Wholesale Trade-durable Goods Wholesale trade-non-durable goods Building materials, hardware, garden supply, and mobile home dealers General merchandise stores Apparel and accessory stores Home furniture, furnishings, and equipment stores Miscellaneous retail Textile mill products
13 8
51 52
53 56 57 59 20 Textile and fabric manufacturers (FBM) 22
7 7 8 8 8
Apparel and other nished products made from fabrics and similar materials Transportation equipment
Transportation equipment manufacturers (TRM) Wood and lumber manufacturers (WDM)
Lumber and wood products, except furniture Furniture and xtures
groups were clustered into one group and 20 commercial/government SIC code groups were clustered into one group. These 22 SIC codes primarily generated paper and food wastes. As shown by the groupings in Table 15.6, logical groupings were made using the multivariate cluster analysis. For example, agricultural SIC codes, similar manufacturing SIC codes, and service oriented businesses were clustered together.
SUMMARY OF WASTE CHARACTERIZATION FINDINGS
ORGANICMEAN BIOMEAN OILMEAN CDMEAN RUBBERSTD CDSTD FOODMEAN RUBBERMEAN METALMEAN FABRICSTD FABRICMEAN METALSTD WOODMEAN PAPERMEAN BIOSTD OILSTD PLASTICMEAN YARDMEAN PLASTICSTD GLASSSTD ORGANICSTD GLASSMEAN WOODSTD PAPERSTD FOODSTD OCCSTD OCCMEAN YARDSTD
Index of case
Figure 15.9 Cluster parallel coordinate plot example (for the commercial/government waste group).
Plots were created to visually display the results of the cluster analysis. The two types of graphs developed were cluster parallel coordinate plots and cluster pro le plots. The parallel coordinate plots display the z scores for each SIC code population parameter with a line connecting all the scores. The z score is the normalized value for an attribute, as de ned by the normal distribution curve. The z score indicated the number of standard deviations from the mean. A value of zero for a z score marks the average for the complete sample. Overlapping lines indicate similarities and gaps indicate discrepancies. The plot in Fig. 15.9 displays a parallel coordinate plot for the commercial/government waste group. This plot displays the graphical results of the optimal cluster analysis for this group. In the plot, there is one line for each SIC code population in the cluster that connects its z scores for each of the variables. The lines for these 22 SIC code populations all follow a similar pattern: above average values for food, plastic, paper, and so on. The primary ndings from this phase of the research were the determination of companies that generate similar solid waste stream types and compositions, as well as the actual composition percentages. This information is important to begin the next phase of the research, identifying the dominate variables that in uence solid waste quantities for companies that generate similar material compositions.
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