Browsing by Author "Sousa, Vítor"
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- Are municipal waste utilities becoming sustainable? A framework to assess and communicate progressPublication . Fernández Braña, Álvaro; Sousa, Vítor; Ferreira, CéliaA framework of indicators to assess the progress towards sustainability of municipal waste management utilities is developed. Its purpose is to fulfil the need for assessing the performance of municipal waste (MW) management in a simple but comprehensive way—unlike indicators based on individual aspects such as recycling—and including aspects not well considered before, such as waste prevention. The framework is composed of a set of six single indicators, concerning the three dimensions of sustainability: reduction of effectively landfilled MW and reduction of MW generation (environmental component), balance between expenses and revenues and reduction of costs (economic component), accessibility to separate collection and number of complaints (social component). Each indicator consists of an evaluation of the current status of the variable in contrast to a previous situation, with a positive value in case of improvement or negative in case of decline. Then, the values of the individual indicators are combined to obtain a global result. This approach focuses on dynamic progress towards sustainability, complementing the common static indicators. Contrarily to the existing performance indicator schemes, the proposed framework aims at measuring the progress and not the absolute or relative achievement of a waste management utility. The framework was tested on two Portuguese municipalities, proving to be a straightforward application and reliable in guiding stakeholders. Results for the case study showed good performance on economic sustainability, while environmental and social performance were lower due to a lack of strategies for waste prevention and low source separation, affected by poor accessibility to separate collection.
- Benchmarking operational efficiency in waste collection: discussion of current approaches and possible alternativesPublication . Sousa, Vítor; Ferreira, Célia; Fernández Braña, Álvaro; Meireles, I.Efficiency assessment and benchmarking are crucial for managing any organization. However, especially from a regulatory perspective, such efficiency assessment and benchmarking must be unbiased from context-specific issues and should provide an absolute rating, rather than a relative one. The current work reviews the approaches used for performance assessment and benchmarking waste collection services, revealing that the majority are biased and are not absolute, and proposes two alternative context-unbiased and absolute performance indicators, the collection capacity use (CCU) and the segregated waste collection efficiency (SWE). The proposed indicators were calculated for 246 utilities operating in Portugal. The utilities were then ranked accordingly, and their position was compared with the position attained using the equivalent performance indicators in the system currently in use by the Portuguese service regulator. The results reveal ranking differences of over 50 positions and illustrate how misleading the results from context-biased and relative metrics can be.
- Prediction performance of separate collection of packaging waste yields using support vector machinesPublication . Sousa, Vítor; Meireles, I.; Oliveira, Verónica; Ferreira, CéliaUnderstanding the drivers underlying waste production in general, and source-segregated waste in particular, is of utmost importance for waste managers. This work aims at evaluating the performance of support vector machines (SVM) models in the prediction of separate collection yields for packaging waste at municipal level. Two SVM models were developed for a case study of 42 municipalities simultaneously serviced by separate collection of packaging waste and by unsorted waste collection. The “SVM-fxed” model used a fxed set of 5 variables to predict collection yields, whereas the “SVM-optimal” model chose from a pool of 14 variables those that optimized performance, using a genetic algorithm. These SVM models were compared with 3 traditional regression models: the ordinary least square linear (OLS-L), the ordinary least square non-linear (OLS-NL) and robust regression. The robust regression model was further compared against the other regression models in order to assess the infuence of the dataset outliers on the model performance. The coefcient of determination, R2 , was used to evaluate the performance of these models. The highest performance was attained by the SVM-optimal model (R2=0.918), compared to the SVM-fxed model (R2=0.670). The performance of the SVM-optimal model was 42% higher than the best performing regression model, the OLS-NL model (R2=0.646). The diferences in performance among the 3 regression models are small (circa 3%), whereas the exclusion of outliers improved their performance by 13%, indicating that outliers impacted more on performance than the type of traditional regression technique used. The results demonstrate that SVM model can be a viable alternative for prediction of separate collection of packaging waste yields and that there are nine important drivers that all together explain roughly 92% (R2=0.918) of the variability in the separate collection yields data.
- Recolha seletiva de embalagens na região litoral Centro de Portugal: sistema atual vs novas soluçõesPublication . Oliveira, Verónica; Vaz, João; Neves, Anita; Sousa, Vítor; Ferreira, Célia
- A structured methodology to understand municipal waste generation at local level with minimized effort: development and case studyPublication . Fernández Braña, Álvaro; Sousa, Vítor; Ferreira, CéliaUnderstanding municipal solid waste (MSW) generation is a key requirement for designing and optimizing MSW collection services. The present contribution proposes a statistical methodology to identify MSW generation patterns from MSW collection records. The methodology aims at finding statistically distinct household waste generation patterns within the days of the week and within months (seasonal variation). It is based on standard statistical methods (ANOVA complemented by non-parametric tests and cluster analysis). The methodology was applied to a Portuguese neighbourhood to assist in the definition of a waste sampling campaign to support the implementation of a pilot PAYT. The results showed the existence of groups with statistically distinct MSW generation patterns both at the weekly and monthly time scales. Three clusters of days of the week, with high, medium and low generation, and two clusters of months, with high and low generation, were identified. These results allowed to design and implement a customized field waste sampling campaign to estimate the MSW generated at the study site with minimal field work. Instead of implementing a homogeneous sampling campaign (equal number of samples for every day of the week and for every month), the samples were collected from the days and months that showed statistically distinct MSW generation pattern. The systematic procedure can be easily adapted to any given location, thus being a useful tool that combines statistical analysis with field collected data.