Page 254 - Solid Waste Analysis and Minimization a Systems Approach

232 DATA COLLECTION

baseline for the remainder of the data collection due to its high level of detail and
accuracy. The assessment data was compared with data collected using other methods.
These solid waste assessments aided in identifying the variables that aided in solid
waste prediction via preliminary analyses (Franchetti, 1999).
The solid waste assessment procedure involved several steps including a preliminary
questionnaire to collect company information (such as SIC code, days of operation, and
number of employees), a facility walk-through to collect annual waste stream composition
and weight, and data analysis to estimate annual waste stream composition and weights.
The benefits of this data are its high level of accuracy and the ability for the researcher to
contact company representatives for more information or clarification. The drawbacks of
this data collection source and method are its limited nature (limited by the number of
waste assessments that have been conducted by the ECDML) and the high cost and time
associated with conducting more assessments. Possible sources of error associated with
the data collection method are minimal. This is the most thorough and accurate data col-
lection method. One minor possible source of error is related to the sampling method. The
1-day walk-through at each facility assessment to estimate annual generation amounts
may not capture the true amounts or all materials generated. This source of error is min-
imized by interviews with company personnel and waste records review, which verify the
data. The information collected during the assessment is listed below

■ Company name
■ Business focus
■ SIC code
■ Total annual waste composition by weigh and volume
■ Current recycling levels
■ Potential cost and waste reduction improvements
■ Number of employees
■ Annual waste costs

14.5.2 THE INDUSTRIAL WASTE MINIMIZATION PROJECT
(MAHONING COUNTY, OHIO)

Mahoning County developed a project similar to the University of Toledo’s ECDML,
Waste Minimization Research Project. The Industrial Waste Minimization Project
(IWMP), a joint project between Youngstown State University (Ohio) and Mahoning
County (Ohio) conducted no-cost solid waste assessments for Mahoning County busi-
nesses from 1995 until 1998. The IWMP operated with similar goals to the ECDML. The
IWMP conducted on-site audits to estimate annual waste stream weights and composi-
tions of each business surveyed. Environmentally friendly solutions were then developed
to reduce, reuse, or recycle components of the waste stream. In From 1995 until 1998 the
IWMP conducted 46 industrial solid waste audits. The data the IWMP collected included

■ Company name
■ Company contact information