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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 bene ts of this data are its high level of accuracy and the ability for the researcher to contact company representatives for more information or clari cation. 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 collection 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 minimized by interviews with company personnel and waste records review, which verify the data. The information collected during the assessment is listed below
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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
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14.5.2 THE INDUSTRIAL WASTE MINIMIZATION PROJECT (MAHONING COUNTY, OHIO)
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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 businesses 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 compositions 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
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SIC code Service provided or product manufactured Number of employees Volume and weight of the following materials recycled Paper Plastics Styrofoam Cardboard Glass Wood Ferrous metals Nonferrous metals Other materials Additional comments or notes
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A bene t of this data source is its level of detail. A drawback is the dif culty associated with collecting data, as in the ECDML assessments, in particular the high cost and time of each assessment. An assumption from this data is that it is accurate and properly collected. This is also a potential source of error. Contacting and verifying information with the Youngtown State University IWMP manager minimized this potential source of error.
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14.5.3 STATE AND LOCAL GOVERNMENT WASTE SURVEYS
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Many states in the United States have created agencies to monitor and reduce waste generation in their jurisdiction (Arkansas, Indiana, Missouri, New Hampshire, and Ohio). For example, Ohio has created 64 solid waste district throughout the state to monitor and reduce solid waste generation. Several of these solid waste districts conducted industrial surveys to estimate the waste tonnage generated and recycling levels of businesses in their district. The waste tonnage and recycling level reporting are often required by state and federal environmental organizations and aid in measuring progress of waste reduction goals. To begin data collection from the government agencies, a letter was sent to each of ce requesting information on industrial surveys they have conducted. Upon receiving responses from many of the districts, follow-up phone calls were made to each responding District. The purposes of the phone calls were to clarify the information desired for the research and provide delivery instructions. Table 14.2 lists the solid waste districts that responded to the letter and the information each district provided. The bene ts of this data source are its abundance (784 businesses surveyed) and the low cost for data collection. Many of the solid waste district directors also pointed out other valuable information sources. One drawback of this data collection method is con dentiality protection of the businesses by the districts. Few districts gave the company names and contact information of the companies they surveyed, making follow-up
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