Geographical Analysis of the Spatial and Temporal Distribution of Solid Waste in Sulaymaniyah City

Authors

  • Shaema Muhamad Abdulla Department of Geography, College of Humanities, University of Sulaimani.
  • Shirwan Omar Rashid Department of Geography, College of Humanities, University of Sulaimani.
  • Rozhan Faraidun Abdullrahman Department of Geography, College of Humanities, University of Sulaimani.

DOI:

https://doi.org/10.66026/852byv77

Keywords:

Environmental pollution, Solid waste, Temporal distribution, spatial distribution, Sulaymaniyah City

Abstract

nvironmental pollution and its consequences have become among the most Environmental pollution and its consequences have become one of the most significant global challenges affecting all parts of the world, particularly in urban areas, where solid waste generation has increased due to population density and the concentration of various human activities. In this context, Sulaymaniyah City represents a clear example of this phenomenon.

This study, entitled “Geographical Analysis of the Spatial and Temporal Distribution of Solid Waste in Sulaymaniyah City,” aims to identify the spatial and temporal variations in solid waste generation within the city, as well as to determine the main factors influencing these variations.

The study adopts both descriptive and analytical approaches and employs Geographic Information Systems (GIS) techniques for data analysis. The results reveal significant variations in the quantities of solid waste during the period (2016–2024), depending on years, seasons, months, and municipal sectors within the city.

The findings also indicate that the highest amount of solid waste was recorded in 2024, reaching (385,671,000) kg per year, while the lowest amount was recorded in 2020, reaching (298,353,000) kg per year. Furthermore, the per capita solid waste generation rate in 2020 was approximately (0.9) kg per day.

Scientific research requires one or more methods to achieve its objectives. In this study, we rely on descriptive methods and statistical analysis, using geographic information systems (GIS).

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Published

2026-08-16