Analysis of the lockdown effects due to the COVID-19 on air pollution in Brescia (Lombardy)

Bontempi, Elza; Carnevale, Claudio; Cornelio, Antonella; Volta, Marialuisa; Zanoletti, Alessandra

doi:10.1016/j.envres.2022.113193

Cited by 19 publications

(10 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It could be due to the effect of the southwest monsoon during the seasonal change in the area. However, this result was consistent with other studies which reported the reduction of PM10 concentration during the lockdown period ( Bontempi et al, 2022 ; Otmani et al, 2020 ; Tobías et al, 2020 ). In contrast, the significant increases of PM10 concentrations were observed from during LSSR to after LSSR period in all observed districts.…”

Section: Resultssupporting

confidence: 93%

RETRACTED: Impact of COVID-19 Pandemic on Traffic Volume and Air Quality in Urban Areas

Rendana

Idris

Rahim

et al. 2022

Air, Soil and Water Research

View full text Add to dashboard Cite

The large transmission of COVID-19 has resulted in a deep impact on the surrounding urban environments, especially on air quality and traffic flows. The objective of this study was to analyze air pollutant concentrations (PM10, SO2, NO2, CO, and O3) and traffic volumes at five congested districts (Bundaran HI, Kelapa Gading, Jagakarsa, Lubang Buaya, and Kebon Jeruk) within Jakarta city impacted by the large-scale social restriction (LSSR) policy. Air quality data during three periods; before, during, and after the LSSR at five observed districts was obtained from the Department of Environment of Jakarta using the Air Quality Monitoring (AQMS) tool. While vehicle speed data were obtained from the waze data during the study period. In this study, air pollutant data during three periods; before, during, and after the LSSR were compared with vehicle speed and meteorological data using a statistical analysis. Results revealed the mean traffic volume at all five districts has greatly reduced by 19% from before to during the LSSR period. It was consistent with the mean PM10, NO2, CO, and SO2 concentrations which also dropped about 46%, 45%, 30%, and 23% respectively. In contrast, the concentrations of air pollutants significantly increased after the LSSR period. During the LSSR period, the traffic volume was negatively associated with the O3 concentration ( r = −.86, p < .01), it was different with before the LSSR periods where the traffic volume associated with CO ( r = .88, p < .01) and NO2 ( r = .89, p < .01). The broad analysis of changes in air pollutants and traffic volumes can be used by the authorities to arrange a good air quality management and an effective way for current and future scenarios.

show abstract

Section: Resultssupporting

confidence: 93%

RETRACTED: Impact of COVID-19 Pandemic on Traffic Volume and Air Quality in Urban Areas

Rendana

Idris

Rahim

et al. 2022

Air, Soil and Water Research

View full text Add to dashboard Cite

show abstract

“…This difference is close to zero in the case of the optimal regARMA model and is estimated to be around -5µg/m 3 in the other two cases. The reduction estimated with HDGM is the only one consistent with that estimated in other studies (Lonati and Riva, 2021;Bontempi et al, 2022). Second, the abnormal concentrations of HDGM were the least volatile among the four.…”

Section: Spatio-temporal Modelling and Diagnosticssupporting

confidence: 88%

Spatio-temporal Event Studies for Air Quality Assessment under Cross-sectional Dependence

Maranzano¹,

Pelagatti²

2022

Preprint

View full text Add to dashboard Cite

Event Studies (ES) are statistical tools that assess whether a particular event of interest has caused changes in the level of one or more relevant time series. We are interested in ES applied to multivariate time series characterized by high spatial (cross-sectional) and temporal dependence. We pursue two goals. First, we propose to extend the existing taxonomy on ES, mainly deriving from the financial field, by generalizing the underlying statistical concepts and then adapting them to the time series analysis of airborne pollutant concentrations. Second, we address the spatial cross-sectional dependence by adopting a twofold adjustment. Initially, we use a linear mixed spatio-temporal regression model (HDGM) to estimate the relationship between the response variable and a set of exogenous factors, while accounting for the spatio-temporal dynamics of the observations. Later, we apply a set of sixteen ES test statistics, both parametric and nonparametric, some of which directly adjusted for cross-sectional dependence. We apply ES to evaluate the impact on NO 2 concentrations generated by the lockdown restrictions adopted in the Lombardy region (Italy) during the COVID-19 pandemic in 2020. The HDGM model distinctly reveals the level shift caused by the event of interest, while reducing the volatility and isolating the spatial dependence of the data. Moreover, all the test statistics unanimously suggest that the lockdown restrictions generated significant reductions in the average NO 2 concentrations.

show abstract

“…In a similar study evaluating the air quality of 20 major cities around the world, the percentage reductions in air pollutant concentrations were found to be PM 10 (22.4%), PM 2.5 (22.6%), and NO 2 (40%) in Paris; PM 10 (28.7%), PM 2.5 (30.1%), and NO 2 (21.9%) in Frankfurt; and PM 10 (35.7%), PM 2.5 (36.6%), and NO 2 (39%) in London (Sannigrahi et al, 2021 ). In cities, restricting travel intensity and increasing control measures lead to significant reductions in air pollutant concentrations (Bontempi et al, 2022 ; Sahraei et al, 2021 ; Wang et al, 2021 ). In particular, PM 2.5 and NO 2 mobility trends show a significant relationship (Li & Tartarini, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

Evaluation of Istanbul from the environmental components’ perspective: what has changed during the pandemic?

Sönmez

Ayvaz

Ercan

et al. 2022

Environ Monit Assess

View full text Add to dashboard Cite

This study aims to determine the 1-year change over the pandemic period in Istanbul, the megacity with the highest population in Turkey, based on environmental components. Among the environmental topics, water consumption habits, changes in air quality, changes due to noise elements, and most importantly, the changes in usage habits of disposable plastic materials that directly affect health have been revealed. The results obtained showed that, in Istanbul, 8.1 × 10 8 gloves should be considered waste, and considering the population living in districts along coastal areas, the number of waste masks that are likely to end up in the sea was 325.648 pieces/day. The results of the air quality and noise measurements during the pandemic showed that reductions in parallel with human activities were recorded with the lockdown effect. The average noise values of the districts along both sides of the Bosporus, where urbanization is concentrated, were between 50 and 59 dB. The precautions taken during the pandemic have had an effective role in reducing air pollution in Istanbul. In the measurements, the parameters with effective reductions were PM 10 (7–47%), PM 2.5 (13–48%), NO 2 (13–38%), and SO 2 (10–56%). As a result, Istanbul’s year of changes during the pandemic period, in terms of water, air, noise, and solid plastic wastes, which are the most important components of the environment, is presented. Supplementary Information The online version contains supplementary material available at 10.1007/s10661-022-10105-9.

show abstract

Analysis of the lockdown effects due to the COVID-19 on air pollution in Brescia (Lombardy)

Cited by 19 publications

References 26 publications

RETRACTED: Impact of COVID-19 Pandemic on Traffic Volume and Air Quality in Urban Areas

RETRACTED: Impact of COVID-19 Pandemic on Traffic Volume and Air Quality in Urban Areas

Spatio-temporal Event Studies for Air Quality Assessment under Cross-sectional Dependence

Evaluation of Istanbul from the environmental components’ perspective: what has changed during the pandemic?

Contact Info

Product

Resources

About