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MODEL VALIDATION AND CASE STUDY APPLICATION
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Performance Parameters Company 1 (Within Parameters) Lower performance parameter (3s C.L.) Predicted value Upper performance parameter (3s C.L.)
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Actual generation 221 tons Within performance level 207 tons 228 tons
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Performance Parameters Company 2 (Beyond Parameters) Lower performance parameter (3s C.L.) Predicted value Upper performance parameter (3s C.L.) Actual generation 284 tons
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Figure 19.2 Performance parameter case study graphs for company 1 and 2.
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Company 1 generated 221 tons of solid waste annually, which was evaluated as within the performance parameters of 207 and 251 tons. Company 1 was ISO 14001 certi ed and had higher than average disposal costs. Company 1 performed consistently with industry predictions for material composition percentages derived from the integrated model, all within +/ 8 percent of the actual rates. Company 2 generated 284 tons of solid waste annually, which was evaluated as beyond the performance parameters of 231 and 269 tons. Company 2 was not ISO 14001 certi ed and had lower than average disposal costs. Company 2 generated higher than average composition percentages (or actual weights) for several materials, speci cally cardboard and wood. Further analysis of this company found that management did not use returnable containers (this company used disposable containers of wood and cardboard) and engaged in limited waste reduction activities. No recycling manager or coordinator was employed at the company. Figure 19.2 is visual representation of the performance parameter calculations. Companies may use the performance parameters to evaluate and improve waste generation performance. The performance parameters are useful to management to ef ciently and con dentially identify superior and inferior waste management practices.
COST-BENEFIT ANALYSIS CASE STUDY
19.5 Cost-Bene t Analysis Case Study
A cost-bene t analysis was conducted on the out of control company as determined from the performance parameters discussed in the previous section. This was to demonstrate the potential cost savings and revenues that could be generated from increased recycling. Such an analysis serves as an incentive to company management to increase recycling. The analysis was conducted using the actual annual totals of non recycled materials generated by the company. The national average land ll disposal cost, as of April 2003, of $41 per ton was used for the calculations. National averages for recycling commodities were used to calculate the potential revenues generated from the sale of recyclables. These prices were gathered from Recycler s World as of April 2003 (www.recycle.net/price). As shown in Table 19.5, the out of control company could annually avoid $7,624 in land ll disposal costs and generate $22,734 from the sale of recyclables. This amounts to a total annual savings of $30,359 from increased recycling. This potential cost bene t serves as an incentive to management to increase recycling, which would both improve the economics for the company and bene t the environment.
TABLE 19.5 POTENTIAL COST BENEFITS FROM INCREASED RECYCLING FOR SPECIFIED OUT OF CONTROL COMPANY NON RECYCLED WASTE GENERATED PER YEAR (TONS)
MATERIAL
DISPOSAL COST AVOIDANCE PER YEAR (AT $41/TON)
MARKET VALUE PER TON
REVENUE PER YEAR FROM SALE OF RECYCLABLES
TOTAL ANNUAL COST BENEFITS
MOP Newspaper LDPE PP PS HDPE PET Ferrous metals Nonferrous metals Aluminum cans OCC Wood Glass Totals
65.3 8.5 8.4 9.3 9.7 6.4 8.5 5.2 7.8 5.7 22.7 19.9 8.5 186.0
$2,678 $349 $344 $381 $398 $262 $349 $213 $320 $233 $932 $815 $349 $7,624
$1 $6 $130 $55 $50 $130 $55 $85 $1,420 $1,160 $45 $5 $1
$65 $47 $1,092 $512 $485 $832 $469 $442 $11,076 $6,589 $1,022 $99 $4 $22,734
$2,743 $396 $1,436 $893 $883 $1,094 $818 $655 $11,396 $6,822 $1,954 $914 $354 $30,359
MODEL SUMMARY AND RECOMMENDATIONS FOR FUTURE RESEARCH
20.1 Introduction
The goal of this research was to build a model to better understand and evaluate solid waste generation rates of companies and government agencies in the United States. This goal was attained by gathering data, characterizing businesses, and developing mathematical models for companies and government agencies to evaluate individual company waste generation. Figure 20.1 displays the research summary. This chapter discusses the hypothesis testing results, research contributions and limitations, and recommendations for future research.
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