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

Abstract

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.

Evolution of COVID-19 municipal solid waste disposal behaviors using epidemiology-based periods defined by World Health Organization guidelines

“… Urban and Nakada (2021) found that solid waste generation decreased in Brazilian cities when temporary COVID-19 health measures were in effect. A similar decline in waste generation in Lisbon was documented by Sarmento et al (2022) . In contrast, Filho et al (2021a) reported a higher waste generation rate in connection with an increased consumption of packed foods among 204 participants from 23 countries, and an abrupt influx of plastic packaging waste in the residential waste stream ( Filho et al, 2021b ).…”

“…On the other hand, more home cooking with cautious meal planning reduced residential food waste generation during COVID-19 ( Laila et al 2021 a, Rodgers et al 2021 ). A decline in overall waste generation rates is also reported by Urban and Nakada (2021) and Sarmento et al (2022) . These opposing factors likely affected households in different ways, explaining the higher data variabilities in the Group II period.…”

A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19

“…In a Canadian capital city, a significant increase in residential waste was observed during the early waves of the pandemic ( Richter et al., 2021b ). The reported increase in the residential waste collection during COVID-19 corresponds well with the regulators’ administrative measures restricting business operations and commercial activities ( Zambrano-Monserrate et al., 2020 ; Sarmento et al., 2022 ). The widely adopted work-from-home arrangement, social distancing, restricted traveling, and self-isolation may have also resulted in more residential waste.…”

“…(2022) reviewed 9206 papers on smart cities and sustainable development goals (SDG) and found that “waste management” were commonly discussed in SDG studies. Given its significance, many studies have reported the effects of COVID-19 on various waste management issues ( Mahmud et al., 2022 ; Requena-Sanchez et al., 2022 ; Sarmento et al., 2022 ). The literature suggest that the generation and collection of MSW emerged differently under different administrative measures throughout the stages of pandemic.…”

“…Seasonal variations of MSW generation characteristics and recycling behaviors have been well documented and discussed ( Denafas et al., 2014 ; Edjabou et al., 2018 ), and various numerical models have been proposed ( Adusei et al., 2022a , 2022b ; Sarmento et al., 2022 ). Many waste researchers have applied Seasonal Autoregressive Integrated Moving Average (SARIMA) models in quantitative forecasting due to the model's ability to capture seasonal and non-stationary behaviors of time series.…”