Search

The successful design and operation of in situ treatment systems using air and water additions for sustainable landfilling are constrained by a lack of knowledge of the key parameters, such as field air permeability and hydraulic conductivity of landfilled municipal solid waste (MSW). This work provides data on the field air permeability k a and hydraulic conductivity K w of MSW obtained by conducting short-term air and water injection tests at a landfill in Beijing, China. The k a and K w values are found to in the range of 1.2 × 10−13−1.9 × 10−12 m2 and 5.9 × 10−7−7.2 × 10−6 m s−1, respectively. Both k a and K w decreased significantly with landfill depth due to the increase in overburden pressure and the finer particles of the waste in deeper layers, leading to a lower porosity of waste. The higher moisture saturation in the deeper layers also contributed to the decrease in k a. To compare the permeability with respect to air and water, the water permeability k w was calculated based on the estimated K w and was found to be approximately three orders of magnitude smaller than the corresponding k a for waste at the same layer. The differences in k w and k a may be due to the relative air permeability, the potential short-circuiting of air and active production of biogas, which undermine the relationship between k w and k a. Therefore, to successfully design and operate air and water addition systems in a landfill, in situ measurements of the air permeability and hydraulic conductivity are essential. [Copyright &y& Elsevier]

• Accurately determining seasonal change in bulk-density based waste identification. • Residual waste threshold was <114 kg/m3 with good seasonal homogeneity. • Food waste was divided into two: >193 and >211 kg/m3 in winter and summer. • Watermelon pericarp is the dominant subcomponent control of seasonal difference. • Efficiently separating the two wastes will be beneficial for resource recycling. Bulk density is an effective evaluation criterion for food and residual household solid waste (HSW) source separation accuracy, but the effect of seasonal components on its variation is unknown. The objective was to accurately determine seasonal variation in bulk-density based waste identification and to ascertain the dominant controlling subcomponents in food waste leading to seasonal variation. A total of 540 bagged wastes were collected in Beijing in August and December representing summer and winter half year. Low-valued food and residual waste were the primary categories, accounting for 60% and 35% of HSW, respectively. Average residual waste threshold was <114 kg/m3, irrespective of season, with good homogeneity (p =1.000). For food waste, winter thresholds were all lower than summer in investigated communities, appearing relatively seasonal difference (p =0.102), so they were divided into two: >193 kg/m3 in winter and >211 kg/m3 in summer. Mixed waste thresholds were 114-193 and 114-211 kg/m3 in winter and summer, respectively. Moreover, the pericarp moisture remarkably changes with season (p <0.005) while other subcomponents remain unaffected. Frequency distribution of pericarp species further indicate a higher frequency of watermelon pericarp in summer leads to greater food waste moisture than in winter, and therefore significant bulk density threshold differences between seasons. Understanding seasonal change in bulk density identification provides a theoretical basis for 'intelligent supervision trashcan' application in various climate areas across China, further realizing more efficient residual and food waste resource recovery. [ABSTRACT FROM AUTHOR]

• A novel bulk density-based recognition method for kitchen and dry waste. • Wastes physical properties were analyzed by ANOVA and linear regressions. • Dry, mixed, and kitchen waste are discriminated as: <115, 115–211 and > 211 kg/m3. • Source-separated community was observed to determine the feasibility method. Identification technology of household kitchen and dry solid waste has played a major part in improving the accuracy of residents' separation by intelligent outdoor trashcan, which is an effective integral solid waste management tool for growing household solid waste (HSW). Our study aims to present a novel and simple recognition method for kitchen and dry waste based on bulk density. In three communities in Beijing, 270 bagged waste samples were collected, and their moisture content, separation accuracy, and bulk density, characterized. Then a bulk density index was developed to straightforwardly express residents' waste source separation accuracy by linear regression analysis above physical properties. In the 3 Beijing communities, we demonstrated a clear distinction in the bulk density index, for dry, mixed, and kitchen waste of <115, 115–211, >211 kg/m3, respectively. Our results provide a theoretical basis for the establishment of an intelligent waste supervision system, which is of great significance for waste management in developing countries like China. [ABSTRACT FROM AUTHOR]