Air Quality Change in Seoul, South Korea under COVID-19 Social Distancing: Focusing on PM2.5

Han, Beom Soon; Park, Kyeongjoo; Kwak, Kyung-Hwan; Park, Seung Bu; Jin, Han; Moon, Sungju; Kim, Jong-Won; Baik, Jong Jin

doi:10.3390/ijerph17176208

Cited by 44 publications

(38 citation statements)

References 27 publications

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“…Different findings in the context of Korea could be explained by the sufficiently lower levels of air pollutants than many other areas. Moreover, the levels of PM 2.5 , PM 10 , NO 2 and CO after social distancing were reported to decrease by 45.5%, 35.6%, 20.4% and 17.3%, respectively [42, 43]. We, therefore, hypothesised that the magnitude of the association between air pollutant concentrations and COVID‐19 transmission might be underestimated.…”

Section: Discussionmentioning

confidence: 99%

Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea

Hoang

Nguyen

Tran

2021

Tropical Med Int Health

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Objectives This study aimed to examine the association between six air pollutants and COVID‐19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea. Methods We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM2.5, PM10, O3, NO2, CO and SO2) and four meteorological factors (temperature, wind speed, humidity and air pressure) were obtained on seven days prior to the research period. The generalised additive model and the distributed lag nonlinear model were applied to generate the relative risks (RRs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random‐effects model. Results We found that NO2 concentration was positively associated with daily confirmed cases in both Seoul‐Gyeonggi and Daegu‐Gyeongbuk clusters, with RRs (95% CIs) of 1.22 (1.03–1.44) and 1.66 (1.25–2.19), respectively. However, SO2 concentration was observed to be associated with daily confirmed cases in the Seoul‐Gyeonggi cluster only (RR = 1.30, 95% CI = 1.10–1.54), whereas PM2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu‐Gyeongbuk cluster only (RR = 1.14, 95% CI = 1.02–1.27 and RR = 1.30, 95% CI = 1.15–1.48, respectively). Conclusions Our data found that NO2 concentration was positively associated with daily confirmed cases in both clusters, whereas the effect of PM2.5, CO and SO2 on COVID‐19 infection in two clusters was different.

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Section: Discussionmentioning

confidence: 99%

Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea

Hoang

Nguyen

Tran

2021

Tropical Med Int Health

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“…China: (Agarwal et al, 2020;Chauhan and Singh, 2020;Chen et al, 2020a;Chen et al, 2020c;Chen et al, 2020d;Fan et al, 2020;G Huang and Sun, 2020;Lian et al, 2020;Liu et al, 2020c;Miyazaki et al, 2020;Nichol et al, 2020;Pei et al, 2020;Shakoor et al, 2020;Shi and Brasseur, 2020;Silver et al, 2020;Wan et al, 2020;Wang et al, 2020a;Wang et al, 2020b;Wang et al, 2020f;Xu et al, 2020c;Zhang et al, 2020a;Yuan et al, 2021) Other: (Ghahremanloo et al, 2020;Han et al, 2020;Ju et al, 2020;Ma and Kang, 2020;Zhang et al, 2020b) South Asia India: (Bedi et al, 2020;Beig et al, 2020;Biswal et al, 2020;Chatterjee et al, 2020;Gautam et al, 2020;Harshita and Vivek, 2020;Jain and Sharma, 2020;Kant et al, 2020;Kumari and Toshniwal, 2020;Panda et al, 2020;Ranjan et al, 2020;Selvam et al, 2020;Sharma et al, 2020a;Siddiqui et al, 2020;Singh and Chauhan, 2020;…”

Section: East Asiaunclassified

“…The median transportation contribution for Annex I countries was 44% (36%-56%), 14% (8%-19%), and 25% (17%-44%) for the NO x , primary PM 2.5 , and CO emissions, respectively, whereas for Annex II countries, it was 29% (5%-49%), 9% (2%-42%), and 35% (1%-75%). Although the contribution of transportation emissions varied for the above pollutants, it is evident that East Asia China (Agarwal et al, 2020), (Bao and Zhang, 2020), a (Bauwens et al, 2020), (Chen et al, 2020c), (Diamond and Wood, 2020), (Forster et al, 2020), (Gautam, 2020a), (Griffith et al, 2020) (Zhang et al, 2021), (Liu et al, 2020b), (Liu et al, 2020c), (Wang et al, 2021), a (Su et al, 2020), (Miyazaki et al, 2020), (Huang and Sun, 2020), (Wang and Zhang, 2020), (Xu et al, 2020b), a (Park et al, 2020) Japan (Ghahremanloo et al, 2020), (Ma and Kang, 2020), a (Fu et al, 2020) South Korea (Fu et al, 2020), (Han et al, 2020), a (Ju et al, 2020), a (Bauwens et al, 2020), (Ma and Kang, 2020), a (Ghahremanloo et al, 2020) Taiwan (Forster et al, 2020) (continued)…”

Section: "Business As Usual" Emission Inventorymentioning

confidence: 99%

The global impacts of COVID-19 lockdowns on urban air pollution

Gkatzelis

Gilman

Brown

et al. 2021

Elementa: Science of the Anthropocene

137

154

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The coronavirus-19 (COVID-19) pandemic led to government interventions to limit the spread of the disease which are unprecedented in recent history; for example, stay at home orders led to sudden decreases in atmospheric emissions from the transportation sector. In this review article, the current understanding of the influence of emission reductions on atmospheric pollutant concentrations and air quality is summarized for nitrogen dioxide (NO2), particulate matter (PM2.5), ozone (O3), ammonia, sulfur dioxide, black carbon, volatile organic compounds, and carbon monoxide (CO). In the first 7 months following the onset of the pandemic, more than 200 papers were accepted by peer-reviewed journals utilizing observations from ground-based and satellite instruments. Only about one-third of this literature incorporates a specific method for meteorological correction or normalization for comparing data from the lockdown period with prior reference observations despite the importance of doing so on the interpretation of results. We use the government stringency index (SI) as an indicator for the severity of lockdown measures and show how key air pollutants change as the SI increases. The observed decrease of NO2 with increasing SI is in general agreement with emission inventories that account for the lockdown. Other compounds such as O3, PM2.5, and CO are also broadly covered. Due to the importance of atmospheric chemistry on O3 and PM2.5 concentrations, their responses may not be linear with respect to primary pollutants. At most sites, we found O3 increased, whereas PM2.5 decreased slightly, with increasing SI. Changes of other compounds are found to be understudied. We highlight future research needs for utilizing the emerging data sets as a preview of a future state of the atmosphere in a world with targeted permanent reductions of emissions. Finally, we emphasize the need to account for the effects of meteorology, emission trends, and atmospheric chemistry when determining the lockdown effects on pollutant concentrations.

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“…Data processing was performed on raw concentration values, without Due to the progressive enforcement of the restrictive measures since the last week of February, atmospheric emissions varied from day to day, also depending on the pollutants in emissions, compared to their typical values (Supplementary Materials Figure S1). Estimates developed by the Environmental Agency of Lombardia [32] for NOx during the weeks from 9 March to 26 April indicated reductions around a regional average value of about −36%, but ranging between −44% (6)(7)(8)(9)(10)(11)(12) and −20% (9)(10)(11)(12)(13)(14)(15); however, emission reductions in large urban areas in April were −50%, and sometimes −60%. The main contributor to these decreases was the reduction in emissions from road traffic, which was estimated to be around −65% over the entire lockdown period, but −75% at the beginning of April.…”

Section: A B Cmentioning

confidence: 99%

“…Recently, a number of papers have been published reporting the changes in concentration levels for certain pollutants in different areas worldwide, where light or heavy restrictive measures have been implemented [5]. Most of these works refer to China [6][7][8], Korea [9][10][11], India [12], Central [13,14], and South-East Asia [15], but also to Western European countries [16][17][18], Africa [19,20], and North and South America [21][22][23]. The few studies related waste treatment each accounted for 1% of the total annual emissions (about 185 Gg year -1 ).…”

Section: Introductionmentioning

confidence: 99%

Regional Scale Impact of the COVID-19 Lockdown on Air Quality: Gaseous Pollutants in the Po Valley, Northern Italy

Lonati

Riva

2021

Atmosphere

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The impact of the reduced atmospheric emissions due to the COVID-19 lockdown on ambient air quality in the Po Valley of Northern Italy was assessed for gaseous pollutants (NO2, benzene, ammonia) based on data collected at the monitoring stations distributed all over the area. Concentration data for each month of the first semester of 2020 were compared with those of the previous six years, on monthly, daily, and hourly bases, so that pre, during, and post-lockdown conditions of air quality could be separately analyzed. The results show that, as in many other areas worldwide, the Po Valley experienced better air quality during 2020 spring months for NO2 and benzene. In agreement with the reductions of nitrogen oxides and benzene emissions from road traffic, estimated to be −35% compared to the regional average, the monthly mean concentration levels for 2020 showed reductions in the −40% to −35% range compared with the previous years, but with higher reductions, close to −50%, at high-volume-traffic sites in urban areas. Conversely, NH3 ambient concentration levels, almost entirely due the emissions of the agricultural sector, did not show any relevant change, even at high-volume-traffic sites in urban areas. These results point out the important role of traffic emissions in NO2 and benzene ambient levels in the Po Valley, and confirm that this region is a rather homogeneous air basin with urban area hot-spots, the contributions of which add up to a relatively high regional background concentration level. Additionally, the relatively slow response of the air quality levels to the sudden decrease of the emissions due to the lockdown shows that this region is characterized by a weak exchange of the air masses that favors both the build-up of atmospheric pollutants and the development of secondary formation processes. Thus, air quality control strategies should aim for structural interventions intended to reduce traffic emissions at the regional scale and not only in the largest urban areas.

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Air Quality Change in Seoul, South Korea under COVID-19 Social Distancing: Focusing on PM2.5

Cited by 44 publications

References 27 publications

Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea

Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea

The global impacts of COVID-19 lockdowns on urban air pollution

Regional Scale Impact of the COVID-19 Lockdown on Air Quality: Gaseous Pollutants in the Po Valley, Northern Italy

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