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WASTE GROUP
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COMPANIES IN GROUP
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Chemical and rubber manufacturers 2 1 No 14% No 13% 33 34
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OCC, wood
Metal manufacturers
34% 25%
32 33
OCC, wood OCC, wood
Paper manufacturers and printers 8 7 1
Food manufacturers
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Totals
TABLE 17.2 LOWEST 5 PERCENT WASTE GENERATORS IN THE MANUFACTURING WASTE GROUPS (THREE SIGNIFICANT VARIABLES) BASED ON PERFORMANCE PARAMETERS
WASTE GROUP
COMPANIES IN GROUP
NUMBER OF COMPANIES IN THE LOWEST 5% OF WASTE GENERATORS ISO 14001 CERTIFICATION OVERALL RECYCLING LEVEL
LANDFILL DISPOSAL COSTS (DOLLARS PER TON)
LOWER THAN AVERAGE MATERIAL GENERATION VERSUS WASTE GROUP AVERAGES
Chemical and rubber manufacturers 2 1 No 38% Yes 37% 35 41
OCC, wood, plastic OCC, wood, plastic OCC, wood, plastic 39 OCC, wood, plastic
Electronic manufacturers
Textile and fabric manufacturers 1 Yes 41%
Transportation equipment manufacturers 1 Yes
Wood and lumber manufacturers 1 1 Yes Yes
OCC, wood, plastic 68% 51% 35 39 OCC, wood, plastic OCC, wood, plastic
Metal manufacturers
Paper manufacturers and printers 8 7 1
Food manufacturers
OCC, wood, plastic
Totals
300 NUMBER OF COMPANIES IN THE HIGHEST 5% OF WASTE GENERATORS ISO 14001 CERTIFICATION OVERALL RECYCLING LEVEL LANDFILL DISPOSAL COSTS (DOLLARS PER TON) HIGHER THAN AVERAGE MATERIAL GENERATION VERSUS WASTE GROUP AVERAGES
TABLE 17.3 HIGHEST 5 PERCENT WASTE GENERATORS IN THE NONMANUFACTURING WASTE GROUPS (ONE SIGNIFICANT VARIABLE) BASED ON PERFORMANCE PARAMETERS
WASTE GROUP
COMPANIES IN GROUP
Agriculture 1 N/A 11% 29
Organic OCC, metal
Automotive sales, service, and repair 6 1 1 1 1 1 1 1 3 17 N/A N/A N/A N/A N/A N/A N/A N/A 13% 8% 12% 14% 8% 16% 7% 8% N/A 9%
Commercial and government
33 38 41 42 39 35 28 31 34
MOP Wood, OCC MOP OCC Fabric, MOP OCC, plastic MOP MOP OCC
Construction 8 9 7
Education
Food stores
Hotels
Medical services
Recreation and museums
Restaurants
Retail and wholesale
Totals
TABLE 17.4 LOWEST 5 PERCENT WASTE GENERATORS IN THE NONMANUFACTURING WASTE GROUPS (ONE SIGNIFICANT VARIABLE) BASED ON PERFORMANCE PARAMETERS
WASTE GROUP
COMPANIES IN GROUP
NUMBER OF COMPANIES IN THE LOWEST 5% OF WASTE GENERATORS ISO 14001 CERTIFICATION OVERALL RECYCLING LEVEL
LANDFILL DISPOSAL COSTS (DOLLARS PER TON)
LOWER THAN AVERAGE MATERIAL GENERATION VERSUS WASTE GROUP AVERAGES
Agriculture 1 N/A 21%
42 33
Organic OCC, metal
Automotive sales, service, and repair 6 N/A 14%
Commercial and government 1 1 1 1 1 1 1 3 17 N/A N/A N/A N/A N/A N/A N/A N/A 22% 18% 14% 19% 13% 16% 9% 11%
Construction 8 9 7
38 31 42 39 37 33 31 36
Wood, OCC MOP OCC Fabric, MOP OCC, plastic MOP MOP OCC
Education
Food stores
Hotels
Medical services
Recreation and museums
Restaurants
Retail and wholesale
Totals
MODEL DEVELOPMENT AND INTEGRATION
This chapter discusses the integration of the environmental model. A computer program was written based on the characterization analysis, signi cant variable analysis, and performance parameter development. The program integrated the analysis into an environmental model to characterize, quantify, and evaluate solid waste generation of U.S. businesses and government agencies. The program was written using Excel and Visual Basic. Inputs to the program are the independent variables for the company to be analyzed
SIC code Number of employees Land ll disposal cost per ton ISO 14001 certi cation
Output from the program is
Annual solid waste expected mean tonnage Annual waste stream composition tonnages Performance parameters
Figure 18.1 displays a diagram of the model owchart, including data inputs, model processes, and outputs. Bene ts of the program include
Applicable to Internet systems Discrete and con dential for U.S. businesses Waste monitoring and control tool Serves as an incentive for companies to increase recycling by calculating the potential cost bene ts from waste reduction
The integrated environmental model and subsequent programs were utilized to facilitate the validation process and to conduct the case studies discussed in the next chapter.
MODEL DEVELOPMENT AND INTEGRATION
Model Inputs Independent variables for the business or government agency to be analyzed (SIC code, number of employees, landfill disposal cost, ISO 14001 certification)
Model Processes Allocate business or government agency to one of the 20 significant waste groups based on the SIC code input (based on the waste characterization/ cluster analysis)
Waste Group 1 Predict annual solid waste generation tonnage (based on multivariable regression analysis)
Waste Group 2
Waste Group 20
Predict waste stream material tonnages (based on cluster analysis compositions percentages and regression analysis)
Material Tonnages for Group 2
Material Tonnages for Group 20
Establish performance parameters of the business or government agency
Performance Parameters Group 2
Performance Parameters Group 20
Model Outputs Outputs for the business or government agency analyzed: Tonnage predictions for total annual waste generation Tonnage predictions for major annual waste stream components Annual solid waste performance parameters
Model integration owchart.
MODEL VALIDATION AND CASE STUDY APPLICATION
This chapter discusses the validation and provides a demonstration of the integrated environmental model. Two case studies are discussed that demonstrate the application of the performance parameters. The process used to conduct the validation and demonstration of the model is listed below:
1 Collect additional data from existing sources to validate model outputs (a discus-
sion of the additional data collected from the U.S. government and university solid waste programs is provided). 2 Apply the developed regression model using the additional data for several waste groups and conduct hypothesis tests of the regression coef cients at the 95 percent con dence level to validate the developed model regression coef cients. 3 Predict the annual solid waste generation of a business using the developed model and compare the results to actual data to demonstrate the developed model. 4 Conduct two case studies that establish performance parameters for annual waste generation and discuss ndings (one company in control and one out of control).
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