Page 339 - Solid Waste Analysis and Minimization a Systems Approach

RESEARCH CONTRIBUTIONS 317

predicted and characterized using statistical techniques to develop a mathematical
model. This was completed using multivariable regression analysis for the 20 waste
groups and associated statistical validation tests. The number of employees, landfill
disposal costs, and ISO 14001 certification were statistically significant at the 95 percent
confidence level in predicting annual solid waste generation tonnages.

20.2.3 PERFORMANCE EVALUATION AND PREDICTION

The third hypothesis was successfully validated and proved by research results. This
was accomplished by developing confidence intervals based on the regression models
and testing the outputs with two case studies. Individual company solid waste gener-
ation rates were evaluated in a standardized manner by integrating statistical quality
control concepts to monitor and control solid waste generation. This was completed
by integrating confidence intervals mathematics with the waste prediction models for
the 20 waste groups.

20.3 Research Contributions

The largest contribution of this research was the development of the integrated envi-
ronmental model to predict and evaluate solid waste generation of individual U.S.
businesses and government agencies. The analyses conducted combined with the
functionality of the model significantly increased the understanding of solid waste
generation of individual U.S. companies and government agencies. This led to the cre-
ation of new knowledge. Specific contributions are listed below:

■ Objective and rational grouping of businesses that generation similar quantities and
compositions of solid waste.
■ Ability to predict solid waste generation quantities, material tonnages, and recy-
cling levels of most U.S. businesses and government agencies.
■ Standardized evaluation models to monitor and control solid waste generation of
U.S. businesses and government agencies.
■ The integrated environmental model can be programmed on the Internet for confi-
dential usage by businesses to privately evaluate their solid waste generation.
■ Identification of waste generation and recycling trends in the United States and fur-
ther research opportunities based on findings.

The impact of these contributions will significantly aid businesses and environmen-
tal regulators to monitor and control solid waste generation. Businesses may now con-
fidentially evaluate their solid waste generation on an Internet-based system and com-
pare their waste generation to industry-specific benchmarks. This model effectively
and efficiently identifies superior or inferior waste management practices based on
generation rates. Regulators now have an integrated, standardized model to assist in
determining waste generation rates, compositions, and recycling levels of various