| Summary: | Global population growth and booming economies have led to the increasing generation of municipal solid waste (MSW). In 2016, the global MSW generation was 2.01 billion megatons, and this number is anticipated to increase to 2.59 billion and 3.4 billion megatons by 2030 and 2050, respectively. Around 70% of all the generated MSW has been disposed of in landfills (refer to both sanitary landfills and uncontrolled dumpsites herein) globally, resulting in 300,000-500,000 sites worldwide. To ensure the stability and integrity of a landfill, it is necessary to have knowledge of the physical and engineering properties of MSW. Physical properties (such as unit weight and void ratio) and engineering properties (such as compressibility and hydraulic conductivity) are of great concern to engineers and researchers because they are essential for long-term settlement, leachate drainage, and stability assessment of landfills. It is commonly time- and labor-consuming to measure and monitor these properties of MSW in the field and laboratory. Hence, it is meaningful to combine and reanalyze the results of different studies to estimate these difficult-to-obtain properties by using some easily available properties of MSW, for instance, composition. However, there are significant variations in MSW composition in different countries, and even within a single country, changes in lifestyle or the introduction of pre-treatment (e.g., bio-treatment or recycling activities) will have a considerable impact on MSW composition. Therefore, it is beneficial to propose a unified classification system for MSW composition to encourage the comparisons of results from different studies and facilitate the correlations between MSW composition, and the physical and engineering properties of MSW from different countries, which can also deepen our understandings on the properties of MSW.
Chapter 3 proposes a new ternary composition classification method for MSW based on the characteristics and similarities among waste constituents. MSW composition is divided into three fractions, namely, biodegradable (B, paper, food, and yard waste), reinforcing (R, plastics, textile, wood, rubber, and leather), and inert (I, ceramic, glass, metal, gravel, concrete, and soil-like particles) fractions. The ternary composition classification method is applied to estimate the dry unit weight (γd) and void ratio (e) of MSW, based on a comprehensive dataset of 150 reconstituted or synthetic specimens from 54 available studies and 52 in situ MSW specimens from 22 available studies. The quantitative correlations between γd and ternary composition are well established for low-, medium-compacted, and high-compacted MSW, respectively. The γd can be well estimated by ternary composition and compaction effort. The e can be well estimated from the estimated γd.
Chapter 4 proposes a ternary composition-based calculation method for the initial global void ratio (e0*) of MSW for the first time. The calculated e0* values are in good agreement with those calculated using the traditional initial void ratio method. Based on a total of 124 sets of MSW compression data obtained from 44 studies conducted in the laboratory and field, the quantitative correlations between the e0* and the immediate compression index (Cc), secondary compression index induced by mechanical creep (CαM), and secondary compression index induced by bio-compression (CαB) of MSW are evidently established. The Cc can be well estimated by the e0*. The CαM can be well estimated by the e0* and vertical stress (σv). The CαB can be well estimated by the e0*, σv, and biodegradation conditions.
Chapter 5 proposes calculation methods for estimating the total porosity (nt*) and drainable porosity (nd*) of MSW for the first time. The estimated nt* and nd* values match well with the measured total porosity (nt) and drainable porosity (nd). Based on an exhaustive dataset of 38 tests in this thesis plus 410 tests in 59 other studies, the correlations between kS and corresponding measured γd, nt, and nd are established. The kS-nd correlation is more accurate than the commonly used kS-γd and kS-nt correlations. The quantitative correlation between kS and estimated nd* is well established. The MSW kS can be well estimated by nd*. Overall, the new classification system of MSW composition is feasible to estimate the unit weight, void ratio, compressibility, and hydraulic conductivity of a variety of MSW samples with different compositions.
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