Characterization of municipal solid waste in Kuwait: Sector-specific composition analysis and implications.

Abstract

Municipal solid waste (MSW) characterization plays a pivotal role in devising effective waste management strategies conducive to fostering a circular economy. This study presents composition analysis across twenty-four subcategories sourced from residential, commercial, and industrial sectors in Kuwait. The study is conducted in accordance with the Standard Test Method for Determination of the Composition of Unprocessed Municipal Solid Waste (ASTM D5231). The results indicate that organic waste comprises 45.3%, followed by paper waste (19.9%) and plastics (19.8%). The remaining waste comprises glass waste (3.5%), diapers (2.7%), textiles (2.6%) and other waste. Paper waste (19.9%) consists mainly of mixed paper (12.1%), cardboard (3.7%), newspaper (3.3%), printer printouts (0.6%) and other office paper (0.2%). Plastic waste (19.8%) consists mainly of film (11.2%), PET (3.1%), HDPE (1.1%) and other mixed plastics (4.4%). Residential and mixed areas have the highest proportion of organic waste. Commercial areas produce the highest proportion of wastepaper (22.4%) and textiles (3.7%). Industrial areas produce the highest proportion of plastic waste (29.1%), most of which is film (17.3%). The study also provides an overview of the MSW management system in the country, an overview over the legislative framework, and forecasts of future waste generation rates with comparison to historical baselines.Implications: The precise and up-to-date characterization of municipal solid waste is imperative for scholarly journal submissions, as it establishes a foundational understanding of waste composition, aiding researchers and policymakers in the development of effective waste management strategies, resource recovery initiatives, and sustainable solutions to address the evolving challenges in waste management systems.This study provides detailed composition analysis for twenty-four municipal solid waste (MSW) subcategories collected across different sources: residential, commercial, industrial, and mixed areas. Time series forecasting is applied to predict MSW generation based on historical data obtained through the local municipality over the past decade. Factorial analysis is applied to investigate changes across source areas, and a hypothesis test is used to compare the current MSW composition against previous baselines. The results demonstrated significant variation across most waste categories. The plastic waste proportion has increased by 48.5% compared to 2013 data, despite awareness campaigns. Paper waste has also increased in proportion from 6.8% to 16.2%; this increase is associated with the mixed paper subcategory, which is mostly used for packaging. The composition data provided in this study are necessary for long-term monitoring, strategy assessment, and legislation associated with waste reduction and remediation.