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Searching quality data for municipal solid waste planning.

Moe Chowdhury1

  • 1Department of Urban and Regional Planning, Jackson State University, MS 39211, USA. moe.n.chowdhury@jsums.edu

Waste Management (New York, N.Y.)
|May 5, 2009
PubMed
Summary
This summary is machine-generated.

Accurate waste data is crucial for effective recycling and waste management. This study highlights the need for reliable generation statistics to support local planning and regulation, proposing weighing waste at the source as a key solution.

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Area of Science:

  • Environmental Science
  • Waste Management Science
  • Data Science

Background:

  • Effective waste reduction and recycling depend on reliable data for refuse generation and disposal.
  • Current municipal solid waste (MSW) disposal data lacks dependable generation and recycling statistics for planning and regulation.
  • Discrepancies in national waste production data hinder local solid waste planning.

Purpose of the Study:

  • To address the lack of dependable waste generation and recycling statistics.
  • To propose a method for developing sustainable local waste management databases.
  • To provide coefficients for waste generation models.

Main Methods:

  • Collection of waste generation data by weighing samples at generator sites.
  • Development of local databases for various waste categories (residential, commercial, industrial, institutional).
  • Derivation of coefficients from these databases.

Main Results:

  • Identified a critical gap in reliable waste generation and recycling data.
  • Proposed weighing waste at the source as a viable method for data collection.
  • Developed coefficients for waste generation models based on site-specific data.

Conclusions:

  • Weighing waste at the generator site is key to developing sustainable local databases.
  • The developed coefficients can enhance the accuracy of waste generation models.
  • Improved data collection is essential for effective waste management and recycling initiatives.