Analysis and forecasting of municipal solid waste in Nankana City using geo-spatial techniques

  • Shakeel Mahmood
  • Faiza Sharif
  • Atta-ur Rahman
  • Amin U Khan
Article
  • 41 Downloads

Abstract

The objective of this study was to analyze and forecast municipal solid waste (MSW) in Nankana City (NC), District Nankana, Province of Punjab, Pakistan. The study is based on primary data acquired through a questionnaire, Global Positioning System (GPS), and direct waste sampling and analysis. Inverse distance weighting (IDW) technique was applied to geo-visualize the spatial trend of MSW generation. Analysis revealed that the total MSW generated was 12,419,636 kg/annum (12,419.64 t) or 34,026.4 kg/day (34.03 t), or 0.46 kg/capita/day (kg/cap/day). The average wastes generated per day by studied households, clinics, hospitals, and hotels were 3, 7.5, 20, and 15 kg, respectively. The residential sector was the top producer with 95.5% (32,511 kg/day) followed by commercial sector 1.9% (665 kg/day). On average, high-income and low-income households were generating waste of 4.2 kg/household/day (kg/hh/day) and 1.7 kg/hh/day, respectively. Similarly, large-size families were generating more (4.4 kg/hh/day) waste than small-size families (1.8 kg/hh/day). The physical constituents of MSW generated in the study area with a population of about 70,000 included paper (7%); compostable matter (61%); plastics (9%); fine earth, ashes, ceramics, and stones (20.4%); and others (2.6%).The spatial trend of MSW generation varies; city center has a high rate of generation and towards periphery generation lowers. Based on the current population growth and MSW generation rate, NC is expected to generate 2.8 times more waste by the year 2050.This is imperative to develop a proper solid waste management plan to reduce the risk of environmental degradation and protect human health. This study provides insights into MSW generation rate, physical composition, and forecasting which are vital in its management strategies.

Keywords

Municipal solid waste Generation Population Forecasting Geo-visualization GIS 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Shakeel Mahmood
    • 1
  • Faiza Sharif
    • 2
  • Atta-ur Rahman
    • 3
  • Amin U Khan
    • 2
  1. 1.Department of GeographyGovernment College UniversityLahorePakistan
  2. 2.Sustainable Development Study CentreGovernment College UniversityLahorePakistan
  3. 3.Department of GeographyUniversity of PeshawarPeshawarPakistan

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