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

2018 ◽  
Vol 15 (7) ◽  
pp. 1487 ◽  
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%.

scholarly journals Impact of COVID-19 lockdown on the fine particulate matter concentration levels: Results from Bengaluru megacity, India

2021 ◽  
Vol 67 (7) ◽  
pp. 2140-2150
Author(s):  
V. Sreekanth ◽  
Meenakshi Kushwaha ◽  
Padmavati Kulkarni ◽  
Adithi R. Upadhya ◽  
B. Spandana ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Particulate Matter Concentration ◽  
Fine Particulate ◽  
Matter Concentration ◽  
Concentration Levels

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

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.

scholarly journals Fine particulate matter concentration and composition and the incidence of childhood asthma

2021 ◽  
Vol 152 ◽  
pp. 106486
Author(s):  
Éric Lavigne ◽  
Robert Talarico ◽  
Aaron van Donkelaar ◽  
Randall V. Martin ◽  
David M. Stieb ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Childhood Asthma ◽  
Fine Particulate Matter ◽  
Particulate Matter Concentration ◽  
Fine Particulate ◽  
Matter Concentration

Diurnal Patterns in Global Fine Particulate Matter Concentration

2018 ◽  
Vol 5 (11) ◽  
pp. 687-691 ◽  
Author(s):  
Max I. Manning ◽  
Randall V. Martin ◽  
Christa Hasenkopf ◽  
Joe Flasher ◽  
Chi Li
Keyword(s):  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Diurnal Patterns ◽  
Particulate Matter Concentration ◽  
Fine Particulate ◽  
Matter Concentration

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

2019 ◽  
Vol 25 (6) ◽  
pp. 898-907 ◽  
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/m<sup>3</sup> in bus and the minimum exposure concentration was 29 μg/m<sup>3</sup> in closed car. Similarly, the maximum exposure concentration of NO2 was observed to be 312 μg/m<sup>3</sup> in bus and the minimum exposure concentration was 21 μg/m<sup>3</sup> 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.

scholarly journals Visualization of Correlation for Air Pollution Time Series using TAQMN Data

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.

The Impact of The Pico Y Placa Policy On Fine Particulate Matter In Lima, Peru

2021 ◽  
Author(s):  
Yovitza Romero ◽  
Priyanka deSouza ◽  
Fabio Duarte ◽  
Patrick Kinney ◽  
Carlo Ratti ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Fine Particulate Matter ◽  
Vehicular Emissions ◽  
Government Officials ◽  
Pollution Levels ◽  
Particulate Matter Concentration ◽  
Fine Particulate ◽  
The Impact ◽  
The City ◽  
Matter Concentration

Abstract Lima has been ranked among the top most polluted cities in the Americas. Vehicular emissions are the dominant source of pollution in the city. In order to reduce congestion and pollution levels during the XVIII Pan- and Parapan-American Games, Lima government officials enacted the pico y placa policy to restrict the number of vehicles on certain heavily trafficked roads in the city at rush hours between Monday to Thursday based on the last digit of their license plates. This policy was retained after the Games. In this paper we evaluate the impact of this policy on fine particulate matter concentration levels (PM2.5) at a background site in the city using a difference-in-difference approach. We find that the policy resulted in increases on PM2.5 levels on Monday-Thursday compared to Friday-Sunday levels after the policy was enacted, compared to previous years. However, such an increase was not significant. These results suggest the need for additional policies to reduce pollution due to traffic in Lima. It also suggests the need to track the response to this policy over time to evaluate its efficacy.

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