COVID-19 prevention, air pollution and transportation patterns in the absence of a lockdown

Chang, Hung‐Hao; Meyerhoefer, Chad D.; Yang, Fusheng

doi:10.1016/j.jenvman.2021.113522

Cited by 23 publications

(18 citation statements)

References 35 publications

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“…To avoid being infected using shared means of transport, some residents may have preferred to drive private cars instead of public transport, resulting in increased air pollutant emissions. This result is similar to existing literature [ 33 , 34 ] that confirms that the increase in air pollution is due to the shift of the preferred mode of travel from public transport to personal motor vehicles during weekdays. Beginning in May 2020, strict home isolation and travel control policies began to show success.…”

Section: Resultssupporting

confidence: 92%

Changes in Air Quality during the Period of COVID-19 in China

Huang

et al. 2022

IJERPH

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This paper revisits the heterogeneous impacts of COVID-19 on air quality. For different types of Chinese cities, we analyzed the different degrees of improvement in the concentrations of six air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) during COVID-19 by analyzing the predictivity of air quality. Specifically, we divided the sample into three groups: cities with severe outbreaks, cities with a few confirmed cases, and cities with secondary outbreaks. Ensemble empirical mode decomposition (EEMD), recursive plots (RPs), and recursive quantitative analysis (RQA) were used to analyze these heterogeneous impacts and the predictivity of air quality. The empirical results indicated the following: (1) COVID-19 did not necessarily improve air quality due to factors such as the rebound effect of consumption, and its impacts on air quality were short-lived. After the initial outbreak, NO2, CO, and PM2.5 emissions declined for the first 1–3 months. (2) For the cities with severe epidemics, air quality was improved, but for the cities with second outbreaks, air quality was first enhanced and then deteriorated. For the cities with few confirmed cases, air quality first deteriorated and then improved. (3) COVID-19 changed the stability of the air quality sequence. The predictability of the air quality index (AQI) declined in cities with serious epidemic situations and secondary outbreaks, but for the cities with a few confirmed cases, the AQI achieved a stable state sooner. The conclusions may facilitate the analysis of differences in air quality evolution characteristics and fluctuations before and after outbreaks from a quantitative perspective.

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Section: Resultssupporting

confidence: 92%

Changes in Air Quality during the Period of COVID-19 in China

Huang

et al. 2022

IJERPH

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“…Consistent with Barua and Nath ( 2021 ), greater movement across outdoor areas significantly increased the level of pollutant emissions. As well, in line with Chang et al ( 2021 ), the rise of pandemic figures triggered a turn from public transport use to personal vehicle use, hence a boost in pollution. Another justification is related to the expanded usages of household fuel for cooking and heating due to restricted interior events, which boosted the dirty indoor air (Zhang et al, 2022 ).…”

Section: Empirical Findingssupporting

confidence: 78%

Modeling the impact of the COVID‐19 outbreak on environment, health sector and energy market

Armeanu

Gherghina

Vasile

et al. 2022

Sustainable Development

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The global outbreak of COVID‐19 disease had a significant impact on the entire globe. Such a notable public health event can be seen as a “black swan” that brings unpredictable and unusual forces into the economic context and that it could typically lead to a chain of adverse reactions and market disruptions. Hence, the purpose of this study is to examine how COVID‐19 affects the environment, health, and the oil and energy markets. To achieve this objective, we used daily data for several measures that refer to the environment, health, and oil and energy, for the first wave of the COVID‐19 pandemic (December 31, 2019–May 22, 2020). The variable integration mix led to the approach of the ARDL model, and the Granger causality test was also employed. These empirical techniques allowed us to examine the cointegration between variables and causal relationships. The econometric results of the ARDL models exhibited that the global new cases and new deaths of COVID‐19 have short and long‐term effects on the environment, the health sector, the oil, and energy measures. However, no significant causal connection was found between the pandemic and the environment, the health sector, or the oil and energy industry, according to the Granger causality test. The uniqueness of current approach consists in the investigation of pandemic impact on the health, environment, oil, and energy sector by applying the ARDL model that permits the analysis of cointegration both in the long run and in the short term. This study provides important insights for investors and policy makers.

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“…COVID-19 was contained without imposing lockdown or implementing work-from home policies, and its impact on people's daily lives was minimized in 2020 ( Chen and Fang, 2021 ). Consequently, in contrast with most of the reported studies, insignificant changes or higher concentrations of major pollutants (carbon monoxide (CO), sulfur dioxide (SO 2 ), ozone (O 3 ), PM 2.5 and PM 10 ) were observed in Taipei and New Taipei cities (major cities in northern Taiwan) at the early stages of COVID-19 ( Chang et al, 2021 ). However, according to the report from Taiwan's Environmental Protection Administration (TEPA), a substantial improvement in air quality was observed in Taiwan for 2020 compared to 2019 ( TEPA, 2021 ), which may indicate a delayed improvement in the COVID-19 impact on the cities that did not impose lockdown.…”

Section: Introductionmentioning

confidence: 78%