Impact of COVID-19 lockdown measures on waste production behavior in Lisbon.
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ABSTRACT:
SUBMITTER: Sarmento P
PROVIDER: S-EPMC8648666 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The COVID-19 outbreak forced national governments to the adoption of social distancing and movement limitation measures aimed to reduce the diffusion of the virus and to mitigate its highly disruptive impact on the healthcare systems. Reduced income, job insecurity, distribution system interruptions, product shortages, localized price hikes, and time availability resulted in changes in food-related behaviors of households, including food waste generation. Although the significant progress achieved in the understanding of the multidimensional determinants of food losses and waste, no study has been considering the role of uncertainty generated by exogenous generalized shocks on consumer behavior. Building on an original and nationally representative survey, this work aims to investigate the impact of the measures introduced to contain the outbreak of COVID-19 on the main behavioral factors underpinning household food waste generation. The study develops a theoretical model introducing uncertainty validated through a Structural Equations Modelling approach. Results showed that during the quarantine period declared household food waste decreased, with more than half of the respondents reporting to waste less. The model suggested that the amount of material and non-material resources that consumers can dedicate to food-related activities represents the most influential factor for the generation of household food waste and that uncertainty is significantly affecting the drivers and indirectly influencing the self-declared values of food waste. Results suggest several potential policy implications, of which the most relevant being related to the importance of stimulating improvements in food management opportunities at home.
| S-EPMC9758647 | biostudies-literature
Project description:In 2020, most countries around the world have observed varying degrees of public lockdown measures to mitigate the transmission of SARS-CoV-2. As an unintended consequence of reduced transportation and industrial activities, air quality has dramatically improved in many major cities around the world. In this paper, we analyze the environmental impact of the lockdown measures on PM2.5 concentration levels in 48 core-based statistical areas (CBSA) of the United States, during the pre and post-lockdown period of January to June 2020. We model the effect of lockdown on the PM2.5 concentration in different CBSAs while adjusting for various meteorological factors like temperature, wind-speed, precipitation and snow. Linear mixed effects models and functional regression methods with random intercepts are employed to capture the heterogeneity of the effect across different regions. Our analysis shows there is a statistically significant reduction in levels of PM2.5 across most of the regions during the lock-down period, although interestingly, this effect is not uniform across all the CBSAs under consideration.
| S-EPMC8025541 | biostudies-literature
Project description:Stringent lockdown measures implemented in Italy to mitigate the spread of COVID-19 are generating unprecedented economic impacts. However, the environmental consequences associated with the temporary shutdown and recovery of industrial and commercial activities are still not fully understood. Using the well-known carbon footprint (CF) indicator, this paper provides a comprehensive estimation of environmental effects due to the COVID-19 outbreak lockdown measures in Italy. Our aim was to quantify the CF associated with the consumption of energy by any economic activity and region in Italy during the lockdown, and then compare these environmental burdens with the CF calculated for analogous periods from 2015 to 2019 (~March and April). Complementarily, we also conducted a scenario analysis to estimate the post-lockdown CF impact in Italy. A consumption-based approach was applied according to the principles of the established Life Cycle Assessment method. The CF was therefore quantified as a sum of direct and indirect greenhouse gases (GHGs) released from domestically produced and imported energy metabolism flows, excluding the exports. Our findings indicate that the CF in the lockdown period is ~-20% lower than the mean CF calculated for the past. This means avoided GHGs in between ~5.6 and ~10.6 Mt CO2e. Results further suggest that a tendency occurs towards higher impact savings in the Northern regions, on average ~230 kt CO2e of GHGs avoided by province (against ~110-130 kt CO2e in central and Southern provinces). Not surprisingly, these are the utmost industrialized areas of Italy and have been the ones mostly affected by the outbreak. Despite our CF estimates are not free of uncertainties, our research offers quantitative insights to start understanding the magnitude generated by such an exceptional lockdown event in Italy on climate change, and to complement current scientific efforts investigating the relationships between air pollution and the spread of COVID-19.
| S-EPMC7258837 | biostudies-literature
Project description:The lagoon of Venice has always been affected by the regional geomorphological evolution, anthropogenic stressors and global changes. Different morphological settings and variable biogeophysical conditions characterize this continuously evolving system that rapidly responds to the anthropic impacts. When the lockdown measures were enforced in Italy to control the spread of the SARS-CoV-2 infection on March 10th 2020, the ordinary urban water traffic around Venice, one of the major pressures in the lagoon, came to a halt. This provided a unique opportunity to analyse the environmental effects of restrictions to mobility on water transparency. Pseudo true-colour composites Sentinel-2 satellite imagery proved useful for qualitative visual interpretation, showing the reduction of the vessel traffic and their wakes from the periods before and during the SARS-CoV-2 outbreak. A quantitative analysis of suspended matter patterns, based on satellite-derived turbidity, in the absence of traffic perturbations, allowed to focus on natural processes and the residual stress from human activities that continued throughout the lockdown. We conclude that the high water transparency can be considered as a transient condition determined by a combination of natural seasonal factors and the effects of COVID-19 restrictions.
| S-EPMC7242204 | biostudies-literature
Project description:We have investigated the impact of reduced emissions due to COVID-19 lockdown measures in spring 2020 on air quality in Canada's four largest cities: Toronto, Montreal, Vancouver, and Calgary. Observed daily concentrations of NO2, PM2.5, and O3 during a "pre-lockdown" period (15 February-14 March 2020) and a "lockdown" period (22 March-2 May 2020), when lockdown measures were in full force everywhere in Canada, were compared to the same periods in the previous decade (2010-2019). Higher-than-usual seasonal declines in mean daily NO2 were observed for the pre-lockdown to lockdown periods in 2020. For PM2.5, Montreal was the only city with a higher-than-usual seasonal decline, whereas for O3 all four cities remained within the previous decadal range. In order to isolate the impact of lockdown-related emission changes from other factors such as seasonal changes in meteorology and emissions and meteorological variability, two emission scenarios were performed with the GEM-MACH air quality model. The first was a Business-As-Usual (BAU) scenario with baseline emissions and the second was a more realistic simulation with estimated COVID-19 lockdown emissions. NO2 surface concentrations for the COVID-19 emission scenario decreased by 31 to 34% on average relative to the BAU scenario in the four metropolitan areas. Lower decreases ranging from 6 to 17% were predicted for PM2.5. O3 surface concentrations, on the other hand, showed increases up to a maximum of 21% close to city centers versus slight decreases over the suburbs, but Ox (odd oxygen), like NO2 and PM2.5, decreased as expected over these cities.Supplementary informationThe online version contains supplementary material available at 10.1007/s11869-021-01039-1.
| S-EPMC8130219 | biostudies-literature
Project description:Recent studies based on observations have shown the impact of lockdown measures taken in various European countries to contain the Covid-19 pandemic on air quality. However, these studies are often limited to compare situations without and with lockdown measures, which correspond to different time periods and then under different meteorological conditions. We propose a modelling study with the WRF-CHIMERE modelling suite for March 2020, an approach allowing to compare atmospheric composition with and without lockdown measures without the biases of meteorological conditions. This study shows that the lockdown effect on atmospheric composition, in particular through massive traffic reductions, has been important for several short-lived atmospheric trace species, with a large reduction in NO2 concentrations, a lower reduction in Particulate Matter (PM) concentrations and a mitigated effect on ozone concentrations due to non-linear chemical effects.
| S-EPMC7309726 | biostudies-literature
Project description:The COVID-19 pandemic has induced many issues for all societal sectors, in particular in the production and disposal of municipal solid waste. This may be because successive easing and reimposing of lockdown measures have deeply changed people's movements, consumers' behaviors and waste management. Previous studies have focused on the short-term effects of lockdowns on waste changes, yet there is little knowledge on waste variations during successive lockdowns and unlocking of various lockdown intensities. Moreover, the efficiency of lockdown and its relation to people's mobility in different countries are still not clear. Here, we studied the variations of amount and composition of municipal solid waste before the pandemic in 2019 and during the pandemic in 2020-2021 in USA, Brazil, Canada, UK, France and Italy. We used a stringency index and a composite mobility index to assess the lockdown intensity and people's movements. Results show that the mobility index sharply decreased with lockdown intensity, and enforcing measures were more efficient in France and Italy. Compared to 2019, prolonged lockdowns caused larger decreases in the quantity of commercial and construction wastes versus household waste. The initial implementation of lockdown or unlocking measures promoted inhabitants' consumption, generally leading to the increased waste amount, by about 9% for Trento and 12% for Montreal at the beginning of lockdown, respectively. Moreover, larger variations in the waste amount in Trento, from - 25.3 to 9.8%, were in line with higher lockdown intensity compared to those in Montreal, from - 9.5 to 12.7%, affected by people's mobility, consumers' behaviors and waste management.Supplementary informationThe online version contains supplementary material available at 10.1007/s10311-021-01290-z.
| S-EPMC8325046 | biostudies-literature
Project description:BackgroundHow effective have lockdowns been at reducing the covid-19 infection and mortality rates? Lockdowns influence contact among persons within or between populations including restricting travel, closing schools, prohibiting public gatherings, requiring workplace closures, all designed to slow the contagion of the virus. The purpose of the present study was to assess the impact of lockdown measures on the spread of covid-19 and test a theoretical model of the covid-19 pandemic employing structural equation modelling.MethodsLockdown variables, population demographics, mortality rates, infection rates, and health were obtained for eight countries: Austria, Belgium, France, Germany, Italy, Netherlands, Spain, and the United Kingdom. The dataset, owid-covid-data.csv, was downloaded on 06/01/2020 from: https://github.com/owid/covid-19-data/tree/master/public/data. Infection spread and mortality data were depicted as logistic growth and analyzed with stepwise multiple regression. The overall structure of the covid-19 data was explored through factor analyses leading to a theoretical model that was tested using latent variable path analysis.ResultsMultiple regression indicated that the time from lockdown had a small but significant effect (β = 0.112, p< 0.01) on reducing the number of cases per million. The stringency index produced the most important effect for mortality and infection rates (β = 0.588,β = 0.702, β = 0.518, β = 0.681; p< 0.01). Exploratory and confirmatory analyses resulted in meaningful and cohesive latent variables: 1) Mortality, 2) Infection Spread, 3) Pop Health Risk, and 4) Health Vulnerability (Comparative Fit Index = 0.91; Standardized Root Mean Square Residual = 0.08).DiscussionThe stringency index had a large impact on the growth of covid-19 infection and mortality rates as did percentage of population aged over 65, median age, per capita GDP, diabetes prevalence, cardiovascular death rates, and ICU hospital beds per 100K. The overall Latent Variable Path Analysis is theoretically meaningful and coherent with acceptable fit indices as a model of the covid-19 pandemic.
| S-EPMC8491873 | biostudies-literature
Project description:ObjectivesTo assess the potential impacts of successive lockdown-easing measures in England, at a point in the COVID-19 pandemic when community transmission levels were relatively high.DesignWe developed a Bayesian model to infer incident cases and reproduction number (R) in England, from incident death data. We then used this to forecast excess cases and deaths in multiple plausible scenarios in which R increases at one or more time points.SettingEngland.ParticipantsPublicly available national incident death data for COVID-19 were examined.Primary outcomeExcess cumulative cases and deaths forecast at 90 days, in simulated scenarios of plausible increases in R after successive easing of lockdown in England, compared with a baseline scenario where R remained constant.ResultsOur model inferred an R of 0.75 on 13 May when England first started easing lockdown. In the most conservative scenario modelled where R increased to 0.80 as lockdown was eased further on 1 June and then remained constant, the model predicted an excess 257 (95% CI 108 to 492) deaths and 26 447 (95% CI 11 105 to 50 549) cumulative cases over 90 days. In the scenario with maximal increases in R (but staying ≤1), the model predicts 3174 (95% CI 1334 to 6060) excess cumulative deaths and 421 310 (95% CI 177 012 to 804 811) cases. Observed data from the forecasting period aligned most closely to the scenario in which R increased to 0.85 on 1 June, and 0.9 on 4 July.ConclusionsWhen levels of transmission are high, even small changes in R with easing of lockdown can have significant impacts on expected cases and deaths, even if R remains ≤1. This will have a major impact on population health, tracing systems and healthcare services in England. Following an elimination strategy rather than one of maintenance of R ≤1 would substantially mitigate the impact of the COVID-19 epidemic within England.
| S-EPMC8438582 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic led to the UK government enforcing lockdown restrictions to control virus transmission. Such restrictions present opportunities and barriers for physical activity and healthy eating. Emerging research suggests that in the early stages of the pandemic, physical activity levels decreased, consumption of unhealthy foods increased, while levels of mental distress increased. Our aims were to understand patterns of diet, physical activity, and mental health during the first lockdown, how these had changed twelve-months later, and the factors associated with change.MethodsAn online survey was conducted with UK adults (N = 636; 78% female) during the first national lockdown (May-June 2020). The survey collected information on demographics, physical activity, diet, mental health, and how participants perceived lifestyle behaviours had changed from before the pandemic. Participants who provided contact details were invited to complete a twelve-month follow-up survey (May-June 2021), 160 adults completed the survey at both time-points. Descriptive statistics, T-tests and McNemar Chi Square statistics were used to assess patterns of diet, physical activity, and mental health at baseline and change in behaviours between baseline and follow-up. Linear regression models were conducted to explore prospective associations between demographic and psycho-social variables at baseline with change in healthy eating habit, anxiety, and wellbeing respectively.ResultsBetween baseline and follow-up, healthy eating habit strength, and the importance of and confidence in eating healthily reduced. Self-rated health (positively) and confidence in eating healthily (negatively) were associated with change in healthy eating habit. There were no differences between baseline and follow-up for depression or physical activity. Mean anxiety score reduced, and wellbeing increased, from baseline to follow-up. Living with children aged 12-17 (compared to living alone) was associated with an increase in anxiety, while perceiving mental health to have worsened during the first lockdown (compared to staying the same) was associated with reduced anxiety and an increase in mental wellbeing.ConclusionsWhile healthy eating habits worsened in the 12 months since the onset of the pandemic, anxiety and mental wellbeing improved. However, anxiety may have increased for parents of secondary school aged children.
| S-EPMC9354438 | biostudies-literature