Effluent discharges can potentially result in high concentrations of metals entering aquatic environments for short durations, ranging from a few hours to days. The environmental risks of such exposures are challenging to accurately assess. Risk assessment tools for effluent discharges include comparison of toxicant concentrations with guideline values and the use of direct toxicity assessments, both of which were designed to assess continuous, rather than pulse, contaminant exposures. In this study, a chronic pulse-exposure toxicity test was developed using the tropical euryhaline calanoid copepod Acartia sinjiensis. This copepod has a rapid life cycle and is highly sensitive to metal contaminants, with 50% effect concentrations (chronic EC50) for larval development of 1.7, 8.6 and 0.7 μg L-1 for copper, nickel and zinc, respectively. The toxicities of copper and nickel were assessed as a continuous exposure (78 h) and as pulses (3, 6 and 18 h) initiated at varying life stages, from egg to copepodite, and measured larval development over 78 h. Generally, 24-h old nauplii were more sensitive or of similar sensitivity to copper and nickel pulses than 48-h old nauplii. The 78-h test duration enabled observations of chronic effects following pulse exposures, which frequently occurred in the absence of acute effects. The EC50 values for pulse exposures were higher than those of continuous exposure by up to approximately 16-fold and 15-fold for copper and nickel, respectively. When metal-pulse exposure concentrations were expressed using the time-weighted averaged concentration (TAC), resultant concentration response curves were similar to those in continuous exposures to the same metal, suggesting that thresholds based on continuous exposures were also protective for pulse exposures to these metals. This research improves our understanding of the toxicity of pulse contaminant exposures and assists with developing improved approaches to for the risk assessment and regulation of short-term contaminant discharges.Prediction of waste production is an essential part of the design and planning of waste management systems. The quality and applicability of such predictions depend heavily on model assumptions and the structure of the collected data. Ordinarily, municipal waste generation data are organized in hierarchical structures with municipal or county levels, and multilevel models can be used to generalize linear regression by directly incorporating the structure into the model. However, small amounts of data can limit the applicability of multilevel models and provide biased estimates. To cope with this problem, Bayesian estimation is often recommended as an alternative to frequentist estimation, such as least squares or maximum likelihood estimation. This paper proposes a multilevel framework under a Bayesian approach to model municipal waste generation with hierarchical data structures. Using a real-world dataset of municipal waste generation in Denmark, the predictive accuracy of multilevel models is compared to aggregated and disaggregated Bayesian models using socio-economic external variables. Results show that Bayesian multilevel models outperform the other models in prediction accuracy, based on the leave-one-out information criterion. A comparison of the Bayesian approach with its frequentist alternative shows that the Bayesian model is more conservative in coefficient estimation, with estimates shrinking to the grand mean and broader credible intervals, in contrast with narrower confidence intervals produced by the frequentist models.This paper presents a multi-objective optimization (MOO) of waste-to-energy (WtE) to investigate optimized solutions for thermal, economic, and environmental objectives. These objectives are represented by net efficiency, total cost in treating waste, and environmental impact. Integration of the environmental objective is conducted using life cycle assessment (LCA) with endpoint single score method covering direct combustion, reagent production and infrastructure, ash management, and energy recovery. Initial net efficiency of the plant was 16.27% whereas the cost and environmental impacts were 75.63 €/ton-waste and -1.21 × 108 Pt/ton-waste, respectively. A non-dominated sorting genetic algorithm (NSGA-II) is applied to maximize efficiency, minimize cost, and minimize environmental impact. Highest improvement for single objective is about 13.4%, 10.3%, and 14.8% for thermal, economic, and environmental, respectively. These improvements cannot be made at once since the objectives are conflicting. These findings highlight the significance role of decision makers in assigning weight to each objective function to obtain the optimal solution. The study also reveals different influence among decision variable, waste input, and marginal energy sources. Finally, this paper underlines the versatility of using MOO to improve WtE performance regarding the thermal, economic, and environmental aspects without requiring additional investment.In the present study, catalytic fast pyrolysis of waste mixed cloth in an ex-situ method using hierarchical HZSM and commercial CaO was investigated. Pyrolysis of waste mixed cloth in a temperature range of 450 °C to 750 °C mainly allowed for the formation of levoglucosan without any catalysts. The utilization of HZSM with Brønsted/Lewis acid sites on micro- and mesoporous structures significantly contributed to monocyclic/dicyclic chemicals production, mainly referring to monoaromatics and naphthalene-based derivatives, especially in the case of high heating rates and catalyst usages. Furthermore, CaO revealed strong deoxygenation performance for the transformation of waste mixed cloth into low oxygen-containing chemicals, such as ketones, aliphatic hydrocarbons and aromatics. The present research thus highlights a feasible route for the catalytic upgrading of waste mixed cloth into some kinds of value-added chemicals.Efficient waste separation using recycling bins designed appropriately is promising for waste recycles. This study investigated recycling bin designs, in particular color and insert slot, and quantified perceptive preferences toward designs. SR-0813 purchase This study hypothesized that design preference toward recycling bins is affected by past perceptions of recycling bin designs. Design categorization survey for 240 recycling bins used in public spaces shows that popular colors depend on design items and waste types. This study found that highly preferred colors were consistent with frequently used colors in certain design items, which was slot frame color for combustible and incombustible waste bins, and body color for PET bottle bins. Color preferences had statistically significant correlations with color usage rates (p = 0.009 for combustible waste bin, p = 0.032 for incombustible waste bin, and p = 0.012 for PET bottle bin, respectively). Although insert slot shape had moderate but significant correlations between slot shape preference and usage rate of slot shape (p = 0.