Expected Health Effects of Reduced Air Pollution from COVID-19 Social Distancing

Cicala, Steve; Holland, Stephen P.; Mansur, Erin T.; Muller, Nicholas Z.; Yates, Andrew J.

doi:10.3390/atmos12080951

Cited by 21 publications

(13 citation statements)

References 30 publications

(40 reference statements)

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“…The reduction of Air Pollutants, even if transient, aroused the interest of researchers in evaluating the potential health benefits arising from scenarios for improving environmental quality (Cicala et al 2021;Perera et al 2021;Tavella et al 2021a, b). This is due to the fact that air pollution is recognized as a contributing factor to mortality from various cardiovascular, respiratory and cerebrovascular diseases (Qingquan et al 2020;Karimi and Shokrinezhad 2021).…”

Section: Introductionmentioning

confidence: 99%

“New Normal”: The Dynamics of Air Pollutants on the Interruption–Recovery Pattern Related to the COVID-19 Pandemic in Recife, Northeastern Brazil

Júnior

2022

Aerosol Sci Eng

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Recife, located in Northeastern Brazil, was one of the first cities in the country to suffer the devastating effects of the COVID-19 Pandemic. The strict measures adopted in the first months of the pandemic seem to have had results and the city had a second wave less intense than other Brazilian capitals. This condition allowed a series of measures to make human activities more flexible until September 2021. In this context, the aim of the study was to evaluate the behavior of Air Pollutants between the months of May 2020 and September 2021, observing the timeline of Interruption-Recovery of economic activities. The concentrations of pollutants (O 3 , NO 2 , SO 2 , PM 2.5 , PM 10 and CO) were obtained by satellite, as well as meteorological variables, used to predict the levels of pollutants in the year 2021 using machine learning. The comparison of monthly averages of pollutants between 2020 and 2021 showed a significant increase in NO 2 , SO 2 , PM 2.5 , PM 10 and CO, in addition to a decrease in O 3 concentrations. Estimated data for the year 2021 from machine learning showed that the levels of NO 2 , SO 2 , PM 2.5 , PM 10 and CO were higher than expected at 15.9%, 14.6%, 25.9%, 15.3% and 2.2%, respectively, while O 3 levels were 6.7% lower than expected. The results show the return of pollutant levels (except O 3 ) to higher levels compared to those measured in the months of greater restriction of human mobility, a behavior similar to that found in other parts of the world.

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Section: Introductionmentioning

confidence: 99%

“New Normal”: The Dynamics of Air Pollutants on the Interruption–Recovery Pattern Related to the COVID-19 Pandemic in Recife, Northeastern Brazil

Júnior

2022

Aerosol Sci Eng

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“…As our sample cities are either the largest metropolises or provincial capital cities in China, business activities are closely reflected by traffic flows. Additionally, it has been shown that the changes in air pollution during the COVID‐19 pandemic are strongly correlated with reduced vehicle travel (Cicala et al., 2021 ) and, consequently, business activities. We use the daily air pollution index PM 2.5, as it is the most utilized air pollution index in China.…”

Section: Data and Empirical Strategymentioning

confidence: 99%

Is no news bad news? The impact of disclosing COVID‐19 tracing information on consumer dine out decisions

Gao

López

Liao

et al. 2022

Agricultural Economics

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Food markets around the world have been disrupted by the COVID‐19 pandemic via consumer behavior upended by fear of infection. In this article, we examine the impact of disclosing COVID‐19 contact tracing information on food markets, using the restaurant industry in China as a case study. By analyzing transaction data at 87 restaurants across 10 cities, we estimate difference‐in‐difference (DID) models to ascertain the impact of COVID‐19 infections and contact information tracing on economic activity as measured by a daily number of transactions. Empirical results show that while the overall number of new COVID‐19 infections at the national level caused a dramatic drop in numbers of transactions in all restaurants, restaurants in cities that disclosed contact tracing information of COVID‐19 infections experienced a 23%–35% higher number of transactions than the ones in cities that did not disclose such information during the recovery period. Ultimately, we show that in the absence of a shelter‐in‐place mandate, disclosing contract tracing information to mitigate consumers’ uncertainties about risks of being infected can contribute to a faster recovery of food markets, in addition to reducing COVID‐19 infections.

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“…StreetLight provided the average VMT for January as the reference under normal situations. Before this study, the StreetLight VMT dataset was widely used as the social distancing or movement indicator to examine the association with conventional health behaviors ( 5 ), policy intervention effects ( 3 ), air pollution ( 30 , 31 ), and pandemic transmission ( 32 ). This study chose StreetLight data as the mobility data source based on the county-level coverage.…”

Section: Datamentioning

confidence: 99%

Mobility Dynamics amid COVID-19 with a Case Study in Tennessee

Hoseinzadeh

Zhang

et al. 2021

Transportation Research Record: Journal of the Transportation R

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The year 2020 has marked the spread of a global pandemic, COVID-19, challenging many aspects of our daily lives. Different organizations have been involved in controlling this outbreak. The social distancing intervention is deemed to be the most effective policy in reducing face-to-face contact and slowing down the rate of infections. Stay-at-home and shelter-in-place orders have been implemented in different states and cities, affecting daily traffic patterns. Social distancing interventions and fear of the disease resulted in a traffic decline in cities and counties. However, after stay-at-home orders ended and some public places reopened, traffic gradually started to revert to pre-pandemic levels. It can be shown that counties have diverse patterns in the decline and recovery phases. This study analyzes county-level mobility change after the pandemic, explores the contributing factors, and identifies possible spatial heterogeneity. To this end, 95 counties in Tennessee have been selected as the study area to perform geographically weighted regressions (GWR) models. The results show that density on non-freeway roads, median household income, percent of unemployment, population density, percent of people over age 65, percent of people under age 18, percent of work from home, and mean time to work are significantly correlated with vehicle miles traveled change magnitude in both decline and recovery phases. Also, the GWR estimation captures the spatial heterogeneity and local variation in coefficients among counties. Finally, the results imply that the recovery phase could be estimated depending on the identified spatial attributes. The proposed model can help agencies and researchers estimate and manage decline and recovery based on spatial factors in similar events in the future.

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Expected Health Effects of Reduced Air Pollution from COVID-19 Social Distancing

Cited by 21 publications

References 30 publications

“New Normal”: The Dynamics of Air Pollutants on the Interruption–Recovery Pattern Related to the COVID-19 Pandemic in Recife, Northeastern Brazil

“New Normal”: The Dynamics of Air Pollutants on the Interruption–Recovery Pattern Related to the COVID-19 Pandemic in Recife, Northeastern Brazil

Is no news bad news? The impact of disclosing COVID‐19 tracing information on consumer dine out decisions

Mobility Dynamics amid COVID-19 with a Case Study in Tennessee

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