Monitoring Air Pollution Variability during Disasters

National environmental regulations lack short-term standards for variability in fine particulate matter (PM2.5); they depend solely on concentration-based standards. Twenty-five years of research has linked short-term PM2.5, that is, increases of at least 10 μg/m3 that can occur in-between regulatory readings, to increased mortality. Even as new technologies have emerged that could readily monitor short-term PM2.5, such as real-time monitoring and mobile monitoring, their primary application has been for research, not for air quality management. The Gulf oil spill offers a strategic setting in which regulatory monitoring, computer modeling, and stationary monitoring could be directly compared to mobile monitoring. Mobile monitoring was found to best capture the variability of PM2.5 during the disaster. The research also found that each short-term increase (≥10 μg/m3) in fine particulate matter was associated with a statistically significant increase of 0.105 deaths (p < 0.001) in people aged 65 and over, which represents a 0.32% increase. This research contributes to understanding the effects of PM2.5 on mortality during a disaster and provides justification for environmental managers to monitor PM2.5 variability, not only hourly averages of PM2.5 concentration.

Download Full-text

Monitoring Air Pollution Variability during Disasters

10.14293/s2199-1006.1.sor-.ppnbbag.v1 ◽

2021 ◽

Author(s):

Earthea Nance

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

New Technologies ◽

Fine Particulate Matter ◽

Air Quality Management ◽

Mobile Monitoring ◽

Short Term ◽

Fine Particulate ◽

Gulf Oil Spill ◽

National Environmental

National environmental regulations lack short-term standards for variability in fine particulate matter (PM 2.5 ); they depend soley on concentration-based standards. Twenty-five years of research has linked short-term PM 2.5 ; that is, increases of at least 10 ug/m 3 that can occur in-between regulatory readings, to increased mortality (Di et al, 2017; Staniswalis et al, 2005; Conroy et al, 2001; Schwartz, 1994). Even as new technologies have emerged that could readily monitor short-term PM 2.5 , such as real-time monitoring and mobile monitoring, their primary application has been for research, not for air quality management. The Gulf oil spill offers a strategic setting in which regulatory monitoring, computer modeling, and stationary monitoring could be directly compared to mobile monitoring. Mobile monitoring was found to best capture the variability of PM 2.5 during the disaster. The research also found that each short-term increase (10-μg/m 3) in fine particulate matter was associated with a statistically significant increase of 0.105 deaths (p<0.001) in people aged 65 and over, a result that is in line with other studies. These findings contribute to understanding the effects of PM 2.5 on mortality during a disaster, and they provide justification for environmental managers to monitor the variability of PM 2.5, not only the concentration.

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

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

Non-accidental mortality risk of short-term exposure to fine particulate matter and its components in Tokyo

Environmental Epidemiology ◽

10.1097/01.ee9.0000608888.88110.fc ◽

2019 ◽

Vol 3 ◽

pp. 270-271

Author(s):

Michikawa T ◽

Takami A ◽

Yoshino A ◽

Sugata S ◽

Ueda K ◽

...

Keyword(s):

Particulate Matter ◽

Mortality Risk ◽

Fine Particulate Matter ◽

Short Term ◽

Fine Particulate ◽

Short Term Exposure

Download Full-text

Effect of Short-Term Exposure to Fine Particulate Matter and Temperature on Acute Myocardial Infarction in Korea

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18094822 ◽

2021 ◽

Vol 18 (9) ◽

pp. 4822

Author(s):

Jiyoung Shin ◽

Jongmin Oh ◽

In Sook Kang ◽

Eunhee Ha ◽

Wook Bum Pyun

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Particulate Matter ◽

Fine Particulate Matter ◽

Ambient Air ◽

Cold Season ◽

Short Term ◽

Fine Particulate ◽

Short Term Exposure ◽

The Impact

Background/Aim: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). Methods: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. Results: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003–1.020 for lag 0, RR: 1.010, CI: 1.000–1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October–April) and the warm season (May–September) showed a significant lag 0 effect for AMI cases in the cold season only. Conclusions: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.

Download Full-text