Has COVID-19 Lockdown Affected on Air Quality?—Different Time Scale Case Study in Wrocław, Poland

Turek, Tomasz; Diakowska, Ewa; Kamińska, Joanna

doi:10.3390/atmos12121549

Cited by 8 publications

(5 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the predicted concentrations of PM 2.5 and PM 10 in Shanghai were higher by an average of 60.81% and 43.12% per day, respectively compared to the observed values throughout the lockdown period from 31 March to 1 June 2022. Therefore, COVID-19 lockdown measures in Shanghai can be considered to have a positive impact on air quality, which is similar to the findings of some public studies researching the changes in the levels of PM 2.5 and PM 10 during the lockdown [9,15,[17][18][19][20]. However, unlike other studies, our study regarded predicted concentrations of PM 2.5 and PM 10 during the lockdown period as the concentrations without lockdown measures.…”

Section: Comparison Of Prediction Results With and Without Meteorolog...supporting

confidence: 83%

“…Besides, reductions in surface PM 2.5 and PM 10 were reported in six mega-cities in India during the lockdown period [18,19]. In 2020, PM concentrations at the traffic and background stations are on average 15% and 13.4% lower than in the reference period in Wrocław, Poland [20]. In contrast, in Italy, no decrease in particulate matter (PM 10 or PM 2.5 ) was observed during the first phase of the COVID-19 epidemic [21] and Few sites (2-3 out of 16) experienced statistically significant drops in PM 2.5 in Ontario, Canada [22].…”

Section: Introductionmentioning

confidence: 98%

See 1 more Smart Citation

The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

Zhang

Liu

et al. 2023

Atmosphere

View full text Add to dashboard Cite

The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM2.5 and PM10 during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM2.5 and PM10 during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM2.5 and PM10 during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality.

show abstract

Section: Comparison Of Prediction Results With and Without Meteorolog...supporting

confidence: 83%

Section: Introductionmentioning

confidence: 98%

The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

Zhang

Liu

et al. 2023

Atmosphere

View full text Add to dashboard Cite

show abstract

“…The introduction of the blockade affected the reduction of motor vehicle traffic. As indicated by studies conducted in other Polish cities during the COVID-19 pandemic, traffic at major intersections dropped by several tens of percent compared to 2019, the time before the pandemic, including in Krakow by 40% [ 78 ] and in Wroclaw by almost 30% [ 79 ]. As seen in Table 7 , most of the investigated roads were of the national and provincial type.…”

Section: Resultsmentioning

confidence: 99%

Verification of the Perception of the Local Community concerning Air Quality Using ADMS-Roads Modeling

Szopińska

Cienciała

Bieda

et al. 2022

IJERPH

View full text Add to dashboard Cite

Road transport is one among the sources of air pollution in a city, which results in lowering the comfort of life and increases the occurrence of respiratory diseases. The level of pollutants emitted in the city is variable, and it depends on the type and nature of the source and the manner of land development. For this reason, the purpose of the article is an attempt at a spatial (inner) diversification of a city in terms of air quality, using a study of perception and semantic differentials (SD). The research, which covered the period from June to November 2021, was performed in Kielce—the Polish Smart City—among local experts, people well acquainted with the city and knowledgeable about air quality and the impact of pollution on human health. The results allowed the demarcation of areas with the best and the worst parameters in terms of air quality within the city. Verification of the survey was carried out using the ADMS-Roads (Atmospheric Dispersion Modeling System) software for modeling pollution levels and GIS software, using data on road traffic. The verification allowed checking whether the respondents participating in the research accurately evaluated the city space. The modeling proved that within the two selected areas, the pollution level is similar, and it does not exceed the permitted values. This might indicate that in society there is still low awareness of air quality, particularly in terms of knowing the sources of pollutants and their impact on human health, and perception of areas with the best and the worst air quality was the result of an analysis of the manner of land development and its morphology.

show abstract

“…Li et al [11] assessed the effect of different emergency response levels on air quality in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), and found that the concentration of PM 2.5 , PM 10 , NO 2 , CO, and O 3 were not significantly different during the Level II and III response periods. Tomasz Turek et al [12] demonstrated that restricting anthropogenic activities did not have an impact on long-term changes and trends in air quality in Wroclaw, Poland. In contrast, Elçin Tan [13] found that the average air quality in Istanbul improved by about 17% during the long-term lockdown period (12 March 2020 to 30 June 2021).…”

Section: Introductionmentioning

confidence: 99%

Analysis of Factors Influencing Air Quality in Different Periods during COVID-19: A Case Study of Tangshan, China

Shan

Liu

et al. 2023

IJERPH

View full text Add to dashboard Cite

This study aimed to analyze the main factors influencing air quality in Tangshan during COVID-19, covering three different periods: the COVID-19 period, the Level I response period, and the Spring Festival period. Comparative analysis and the difference-in-differences (DID) method were used to explore differences in air quality between different stages of the epidemic and different years. During the COVID-19 period, the air quality index (AQI) and the concentrations of six conventional air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3-8h) decreased significantly compared to 2017–2019. For the Level I response period, the reduction in AQI caused by COVID-19 control measures were 29.07%, 31.43%, and 20.04% in February, March, and April of 2020, respectively. During the Spring Festival, the concentrations of the six pollutants were significantly higher than those in 2019 and 2021, which may be related to heavy pollution events caused by unfavorable meteorological conditions and regional transport. As for the further improvement in air quality, it is necessary to take strict measures to prevent and control air pollution while paying attention to meteorological factors.

show abstract

Has COVID-19 Lockdown Affected on Air Quality?—Different Time Scale Case Study in Wrocław, Poland

Cited by 8 publications

References 47 publications

The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

Verification of the Perception of the Local Community concerning Air Quality Using ADMS-Roads Modeling

Analysis of Factors Influencing Air Quality in Different Periods during COVID-19: A Case Study of Tangshan, China

Contact Info

Product

Resources

About