Decrease in Ambient Fine Particulate Matter during COVID-19 Crisis and Corresponding Health Benefits in Seoul, Korea

Both domestic emissions and transported pollutants from neighboring countries affect the ambient fine particulate matter (PM2.5) concentration of Seoul, Korea. Diverse measures to control the coronavirus disease 2019 (COVID-19), such as social distancing and increased telecommuting in Korea and the stringent lockdown measures of China, may reduce domestic emissions and levels of transported pollutants, respectively. In addition, wearing a particulate-filtering respirator may have decreased the absolute PM2.5 exposure level for individuals. Therefore, this study estimated the acute health benefits of PM2.5 reduction and changes in public behavior during the COVID-19 crisis in Seoul, Korea. To calculate the mortality burden attributable to PM2.5, we obtained residents’ registration data, mortality data, and air pollution monitoring data for Seoul from publicly available databases. Relative risks were derived from previous time-series studies. We used the attributable fraction to estimate the number of excessive deaths attributable to acute PM2.5 exposure during January to April, yearly, from 2016 to 2020, and the number of mortalities avoided from PM2.5 reduction and respirator use observed in 2020. The average PM2.5 concentration from January to April in 2020 (25.6 μg/m3) was the lowest in the last 5 years. At least −4.1 μg/m3 (95% CI: −7.2, −0.9) change in ambient PM2.5 in Seoul was observed in 2020 compared to the previous 4 years. Overall, 37.6 (95% CI: 32.6, 42.5) non-accidental; 7.0 (95% CI: 5.7, 8.4) cardiovascular; and 4.7 (95% CI: 3.4, 6.1) respiratory mortalities were avoided due to PM2.5 reduction in 2020. By considering the effects of particulate respirator, decreases of 102.5 (95% CI: 89.0, 115.9) non-accidental; 19.1 (95% CI: 15.6, 22.9) cardiovascular; and 12.9 (95% CI: 9.2, 16.5) respiratory mortalities were estimated. We estimated that 37 lives were saved due to the PM2.5 reduction related to COVID-19 in Seoul, Korea. The health benefit may be greater due to the popular use of particulate-filtering respirators during the COVID-19 crisis. Future studies with daily mortality data are needed to verify our study estimates.

Download Full-text

The Combined Effects of Fine Particulate Matter and Temperature on Preterm Birth in Seoul, 2010–2016

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18041463 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1463

Author(s):

Youngrin Kwag ◽

Min-ho Kim ◽

Shinhee Ye ◽

Jongmin Oh ◽

Gyeyoon Yim ◽

...

Keyword(s):

Particulate Matter ◽

Preterm Birth ◽

Pregnant Women ◽

Low Temperatures ◽

Fine Particulate Matter ◽

Temperature Data ◽

Fine Particulate ◽

The Mean ◽

Pm2.5 Exposure ◽

Pm2.5 Concentration

Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM2.5) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010–2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM2.5 concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM2.5 and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM2.5 concentration was used in units of ×10 µg/m3 and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM2.5 exposure and preterm birth, as well as the combined effects of PM2.5 exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM2.5 and temperature data as exposures, which assumes an interaction between PM2.5 and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM2.5 exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061–1.213, p < 0.001). Conclusions: When we assumed the interaction between PM2.5 exposure and temperature exposure, PM2.5 exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.

Download Full-text

A social network analysis of tourism activity patterns among domestic tourists influenced by fine particulate matter (PM2.5) concentration

Korean Journal of Hospitality & Tourism ◽

10.24992/kjht.2021.10.30.07.237 ◽

2021 ◽

Vol 30 (7) ◽

pp. 237-252

Author(s):

Deuk-Hee Park ◽

Chul-Hee Lim

Keyword(s):

Particulate Matter ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Activity Patterns ◽

Fine Particulate Matter ◽

Fine Particulate ◽

Tourism Activity ◽

Pm2.5 Concentration

Download Full-text

Effect of modes of transportation on commuters' exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in Chennai, India

Environmental Engineering Research ◽

10.4491/eer.2019.380 ◽

2019 ◽

Vol 25 (6) ◽

pp. 898-907 ◽

Cited By ~ 2

Author(s):

M. Gokul Raj ◽

S. Karthikeyan

Keyword(s):

Particulate Matter ◽

Nitrogen Dioxide ◽

Urban Community ◽

Fine Particulate Matter ◽

Exposure Concentration ◽

Ambient Particulate Matter ◽

Fine Particulate ◽

The Mean ◽

Maximum Exposure ◽

Pm2.5 Concentration

Daily commuting increases level of contaminants inhaled by urban community and it is influenced by mode and time of commuting. In this study, the commuters’ exposure to ambient particulate matter (PM2.5) and nitrogen dioxide (NO2) was assessed during three modes of travel in six different road stretches of Chennai. The mean distance of road stretches was 25 km and the exposure to pollutants was assessed during peak hours and off-peak hours. The average travel duration was in the range of 39 to 91 min in motorbike, 83 to 140 min in car and 110 to 161 min in bus. Though there was variation on exposure to concentration in modes of transportation, the maximum exposure concentration of PM2.5 was observed as 709 μg/m3 in bus and the minimum exposure concentration was 29 μg/m3 in closed car. Similarly, the maximum exposure concentration of NO2 was observed to be 312 μg/m3 in bus and the minimum exposure concentration was 21 μg/m3 in car. The concentration of elements in PM2.5 was in the order of Si > Na > Ca > Al ≥ K > S ≥ Cd, with Si and Cd concentration as 60% and < 1% of the PM2.5 concentration.

Download Full-text

Visualization of Correlation for Air Pollution Time Series using TAQMN Data

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c6620.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 7922-7927

Keyword(s):

Air Pollution ◽

Time Series ◽

Particulate Matter ◽

Pearson Correlation ◽

Fine Particulate Matter ◽

Correlation Method ◽

Well Being ◽

Pollution Levels ◽

Fine Particulate ◽

Pm2.5 Concentration

In Taiwan country Annan, Chiayi, Giran, and Puzi cities are facing a serious fine particulate matter (PM2.5) issue. To date the impressive advance has been made toward understanding the PM2.5 issue, counting special temporal characterization, driving variables and well-being impacted. However, notable research as has been done on the interaction of the content between the selected cities of Taiwan country for particulate matter (PM2.5) concentration. In this paper, we purposed a visualization technique based on this principle of the visualization, cross-correlation method and also the time-series concentration with particulate matter (PM2.5) for different cities in Taiwan. The visualization also shows that the correlation between the different meteorological factors as well as the different air pollution pollutants for particular cities in Taiwan. This visualization approach helps to determine the concentration of the air pollution levels in different cities and also determine the Pearson correlation, r values of selected cities are Annan, Puzi, Giran, and Wugu.

Download Full-text

Impact of long-term temporal trends in fine particulate matter (PM2.5) on associations of annual PM2.5 exposure and mortality

Environmental Epidemiology ◽

10.1097/ee9.0000000000000009 ◽

2018 ◽

Vol 2 (2) ◽

pp. e009 ◽

Cited By ~ 1

Author(s):

Ki-Do Eum ◽

Helen H. Suh ◽

Vivian Chit Pun ◽

Justin Manjourides

Keyword(s):

Particulate Matter ◽

Fine Particulate Matter ◽

Temporal Trends ◽

Fine Particulate ◽

Pm2.5 Exposure

Download Full-text

Short-Term Associations of Fine Particulate Matter and Synoptic Weather Types with Cardiovascular Mortality: An Ecological Time-Series Study in Shanghai, China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17031111 ◽

2020 ◽

Vol 17 (3) ◽

pp. 1111 ◽

Cited By ~ 1

Author(s):

Qing Tian ◽

Mei Li ◽

Scott Montgomery ◽

Bo Fang ◽

Chunfang Wang ◽

...

Keyword(s):

Particulate Matter ◽

Cardiovascular Mortality ◽

Fine Particulate Matter ◽

Weather Conditions ◽

Cold Weather ◽

Short Term ◽

Weather Types ◽

Synoptic Weather ◽

Fine Particulate ◽

Pm2.5 Concentration

Background: Exposures to both ambient fine particulate matter (PM2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs). Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM2.5. Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM2.5 concentration was 55.0 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM2.5 and SWT, statistically significant interactions were found between PM2.5 and cold weather, with risk for PM2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM2.5 in the 1–3 lag days, while no statistically significant effects were found for other lag day periods. Conclusions: Exposure to PM2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.

Download Full-text

Variation Trends of Fine Particulate Matter Concentration in Wuhan City from 2013 to 2017

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15071487 ◽

2018 ◽

Vol 15 (7) ◽

pp. 1487 ◽

Cited By ~ 5

Author(s):

Daoru Liu ◽

Qinli Deng ◽

Zeng Zhou ◽

Yaolin Lin ◽

Junwei Tao

Keyword(s):

Particulate Matter ◽

Fine Particulate Matter ◽

Wuhan City ◽

Fine Particulate ◽

Variation Patterns ◽

Average Proportion ◽

June July ◽

Matter Concentration ◽

Mean Concentration ◽

Pm2.5 Concentration

Fine particulate matter (PM2.5) is directly associated with smog and has become the primary factor that threatens air quality in China. In order to investigate the variation patterns of PM2.5 concentrations in various regions of Wuhan city across different time spans, we analyzed continuous monitoring data from six monitoring sites in Wuhan city from 2013 to 2017. The results showed that the PM2.5 concentration from the various monitoring sites in the five-year period showed a decreasing trend. January, October, and December are the three months with relatively high mean monthly PM2.5 concentrations in the year, while June, July, and August are the three months with relatively low mean monthly PM2.5 concentrations in the year. The number of days with a daily mean concentration of 35–75 μg/m3 was the highest, while the number of days with a daily mean concentration of more than 250 μg/m3 was the lowest. PM2.5 accounted for a large proportion of the major pollutants and is the main source of air pollution in Wuhan city, with an average proportion of over 46%.

Download Full-text

In Utero Exposure to Fine Particulate Matter Causes Hypertension Due to Impaired Renal Dopamine D1 Receptor in Offspring

Cellular Physiology and Biochemistry ◽

10.1159/000488418 ◽

2018 ◽

Vol 46 (1) ◽

pp. 148-159 ◽

Cited By ~ 7

Author(s):

Zhengmeng Ye ◽

Xi Lu ◽

Yi Deng ◽

Xinquan Wang ◽

Shuo Zheng ◽

...

Keyword(s):

Blood Pressure ◽

Particulate Matter ◽

Sodium Excretion ◽

Fine Particulate Matter ◽

In Utero ◽

D1 Receptor ◽

In Utero Exposure ◽

Fine Particulate ◽

Pm2.5 Exposure ◽

Renal Dopamine

Background/Aims: Adverse environment in utero can modulate adult phenotypes including blood pressure. Fine particulate matter (PM2.5) exposure in utero causes hypertension in the offspring, but the exact mechanisms are not clear. Renal dopamine D1 receptor (D1R), regulated by G protein-coupled receptor kinase type 4 (GRK4), plays an important role in the regulation of renal sodium transport and blood pressure. In this present study, we determined if renal D1R dysfunction is involved in PM2.5–induced hypertension in the offspring. Methods: Pregnant Sprague–Dawley rats were given an oropharyngeal drip of PM2.5 (1.0 mg/kg) at gestation day 8, 10, and 12. The blood pressure, 24-hour sodium excretion, and urine volume were measured in the offspring. The expression levels of GRK4 and D1R were determined by immunoblotting. The phosphorylation of D1R was investigated using immunoprecipitation. Plasma malondialdehyde and superoxide dismutase levels were also measured in the offspring. Results: As compared with saline-treated dams, offspring of PM2.5-treated dams had increased blood pressure, impaired sodium excretion, and reduced D1R-mediated natriuresis and diuresis, accompanied by decreased renal D1R expression and GRK4 expression. The impaired renal D1R function and increased GRK4 expression could be caused by increased reactive oxidative stress (ROS) induced by PM2.5 exposure. Administration of tempol, a redox-cycling nitroxide, for 4 weeks in the offspring of PM2.5-treated dam normalized the decreased renal D1R expression and increased renal D1R phosphorylation and GRK4 expression. Furthermore, tempol normalized the increased renal expression of c-Myc, a transcription factor that regulates GRK4 expression. Conclusions: In utero exposure to PM2.5 increases ROS and GRK4 expression, impairs D1R-mediated sodium excretion, and increases blood pressure in the offspring. These studies suggest that normalization of D1R function may be a target for the prevention and treatment of the hypertension in offspring of mothers exposed to PM2.5 during pregnancy.

Download Full-text

Ambient Fine Particulate Matter and Preterm Birth in California: Identification of Critical Exposure Windows

American Journal of Epidemiology ◽

10.1093/aje/kwz120 ◽

2019 ◽

Vol 188 (9) ◽

pp. 1608-1615 ◽

Cited By ~ 12

Author(s):

Paige Sheridan ◽

Sindana Ilango ◽

Tim A Bruckner ◽

Qiong Wang ◽

Rupa Basu ◽

...

Keyword(s):

Particulate Matter ◽

Preterm Birth ◽

Proportional Hazards ◽

Fine Particulate Matter ◽

Cox Proportional Hazards ◽

Distributed Lag ◽

Fine Particulate ◽

Cox Proportional Hazards Models ◽

Pm2.5 Exposure ◽

Exposure Windows

Abstract Exposure to ambient fine particulate matter (particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5)) during pregnancy is associated with preterm birth (PTB), a leading cause of infant morbidity and mortality. Results from studies attempting to identify etiologically relevant exposure periods of vulnerability have been inconsistent, possibly because of failure to consider the time-to-event nature of the outcome and lagged exposure effects of PM2.5. In this study, we aimed to identify critical exposure windows for weekly PM2.5 exposure and PTB in California using California birth cohort data from 2005–2010. Associations were assessed using distributed-lag Cox proportional hazards models. We assessed effect-measure modification by race/ethnicity by calculating the weekly relative excess risk due to interaction. For a 10-μg/m3 increase in PM2.5 exposure over the entire period of gestation, PTB risk increased by 11% (hazard ratio = 1.11, 95% confidence interval: 1.09, 1.14). Gestational weeks 17–24 and 36 were associated with increased vulnerability to PM2.5 exposure. We find that non-Hispanic black mothers may be more susceptible to effects of PM2.5 exposure than non-Hispanic white mothers, particularly at the end of pregnancy. These findings extend our knowledge about the existence of specific exposure periods during pregnancy that have the greatest impact on preterm birth.

Download Full-text