Network design of a household waste collection system: A case study of the commune of Renca in Santiago, Chile

Study on the Method of Household Waste Collection: Case Study

This article presents research on how household waste is collected. An online survey, with 348 participants, from the Romanian region of Bacau, was conducted from October 2018 to May 2019. The online questionnaire included a set of over 40 questions, some with the aim of identifying the nature of the people participating, but most of the questions being designed to determine the collection methods for household waste. The major goal of the current study, as previously stated, was to determine the primary way of collecting household garbage from the public, while also learning various details about the participants, including their residence location, gender, age, and level of education. Referring to the means used for collecting household waste, the following items were noted: trash cans, cardboard boxes, dumpsters, and raffia bags. As a result of the study carried out, the following conclusions were drawn: it was noticed that 70 percent of those who participated in the survey came from urban areas; a larger percentage of female respondents took part in the survey (128 from 348); the majority of respondents were aged 18–29 (182); 178 respondents had a higher education level; collection of household waste in garbage bags represented 62.9 percent of the total collection methods. Following statistical processing of the data, and an overview of the main ways in which household waste was collected, a number of connections were found between the characteristics of the respondents and their household waste collection. What is noteworthy is that the characteristics of the respondents could be grouped into cumulative factors that played an important role in household waste collection: the first group formed by level of education and location of the respondents, and the second group formed by age and gender of the respondents.

Solving the bin location-allocation problem for household and recycle waste generated in the commune of Renca in Santiago, Chile

In the commune of Renca in Santiago, Chile, the household waste is currently collected on the kerbside and then thrown in the rear of a compactor truck. This system becomes inefficient when not all citizens are always serviced, yielding high overall collection costs and negative impacts on the environment and the society. Recently, recyclable waste collection sites have been situated throughout the commune, which need to be examined with respect to population coverage and average travel distances to these sites. This study employs mixed-integer linear programming models and geographic information systems to solve the bin location-allocation problem for household and recyclable waste separately. The results are shown for different values of waste generation, bin capacities, and travel distances, in addition to considering the users' and municipality's preferences in the decision-making process. The proposed recyclable waste bin locations present a more efficient solution than the existing collection sites in the commune of Renca since more users are serviced within a shorter travel distance to dispose of their recyclable waste.

Impact of COVID-19 lockdown measures on waste production behavior in Lisbon

The recent restrictions on mobility and economic activities imposed by governments due to the COVID-19 pandemic have significantly affected waste production and recycling patterns in cities worldwide. This effect differed both between cities and within cities as the measures of confinement adopted by governments had diverse impacts in different areas of cities, depending on their characteristics (e.g., touristic, or residential). In the present work, mixed waste collection areas were created, based on waste collection points, that define spatial units in which contextual data such as tourism and residential characteristics were aggregated. The difference in mixed waste collected compared with previous years was analyzed along with the impacts on recycling due to the modification in operations regarding waste collection during the lockdown. The results showed that despite the suspension of the door-to-door recycling system during the lockdown, this did not translate into an increase in the production of mixed waste, and the recycling levels of previous years have not been reached after the lockdown, indicating a possible change in recycling habits in Lisbon. The touristic and non-residential mixed waste circuits presented significantly reduced mixed waste production compared to the non-pandemic context. Also, tourist, mobility, and economic activity were measured to understand which factors contributed to waste production changes during the COVID-19 pandemic. While little evidence of a relationship with these exogenous variables was found at the citywide level, evidence was found at the waste collection circuit level.

Evaluate the locations for smart waste bins using BWM and WASPAS methods under a probabilistic linguistic environment

 The decreasing resources of the earth and the deterioration of the environment are offering new challenges for handling waste management practices. The establishment of the smart waste bins plays an important role in promoting the development of waste classification and treatment fundamentally. We developed the evaluation system for the location selection problem of smart waste bins. Considering the uncertainty in the location selection of smart waste bins, the probabilistic linguistic term sets (PLTSs) are selected to express the evaluation information. Because of the excellent performance in weight-determing, the best worst method (BWM) is chosen to get the weight of criteria. While the weighted aggregated sum product assessment (WASPAS) method could handle both the qualitative and quantitative information, which are considered to derive the final ranking of the alternatives. This paper proposed a new group multi-criteria decision making approach integrating the BWM and the WASPAS with probabilistic linguistic information. Finally, in the empirical example, a sensitivity analysis shows that the proposed method is stable, a comparison analysis with PL-TOPSIS, PL-VIKOR, and PL-TODIM reflects its effectiveness and rationality, and the managerial implication verifies its usefulness and practicability, which also give guide to the company, government and resident.

A hybrid mathematical modelling approach for energy generation from hazardous waste during the COVID-19 pandemic

The COVID-19 virus in a short time has caused a terrible crisis that has been spread around the world. This crisis has affected human life in several dimensions, one of which is a sharp increase in urban waste. This increase in waste volume during the pandemic, in addition to the intense increase in costs associated with the risks of virus contagion through infectious waste. In this study, a hybrid mathematical modelling approach including a Bi-level programming model for infectious waste management has been proposed. At the higher level of the model, government decisions regarding the total costs related to infectious waste must be minimized. At this level, the collected infectious waste is converted into energy, the revenue of which is returned to the system. The lower level relates to the risks of virus contagion through infectious waste, which can be catastrophic if ignored. This study has considered the low, medium, high and very high prevalence scenarios as key parameters for the production of waste. In addition, the uncertainty in citizens' demand for waste collection was also included in the proposed model. The results showed that by energy production from waste during the COVID-19 pandemic, 34% of the total cost of collecting and transporting waste can be compensated. Finally, this paper obtained useful managerial insights using the data of Kermanshah city as a real case.