scholarly journals Fine particulate matter (PM2.5) in Ho Chi Minh City: Analysis of the status and the temporal variation based on the continuous data from 2013-2017

2019 ◽  
Vol 2 (5) ◽  
pp. 130-137
Author(s):  
Huy Huu Duong ◽  
Chi Doan Thien Nguyen ◽  
Phu Ly Sy Nguyen ◽  
Hien Thi To

Since 2013, the Ministry of Natural Resources and Environment published the revision of the “National Technical Regulation on Ambient Air Quality” (QCVN 05:2013/BTNMT), in which the fine particulate matter (PM2.5) was added to the QCVN. However, the status and the temporal variation of PM2.5 in Ho Chi Minh City (HCMC) have not been reported so far, especially based on the continuous and high time resolution measurements. The aim of this study was to analyze the status and the temporal variation of PM2.5 collected at the center of HCMC. Based on the composited PM2.5 data from the air monitoring station located at the University of Science, the average PM2.5 concentration was 28.0 ± 18.1 µg/m³ during 2013– 2017. The annual PM2.5 concentration in HCMC exceeded the acceptable limits of QCVN and WHO, highlighting a high human health risk. The PM2.5 concentrations showed the pronounced diurnal variation with the highest observed after the morning rush hour and the lowest during the midnight. In addition, a remarkable seasonal variation was observed with the highest and lowest PM2.5 occurring in dry and rainy seasons, respectively. This result highlighted the vital role of the rainfall events in reducing the PM2.5 level. Finally, from the analysis of the backward trajectories ending at the air monitoring station, we found that the air mass from the North and Northeast originating from China then passing through the areas (i.e. Binh Duong and Dong Nai provinces) with heavy industrial activities possessed a high PM2.5 level.

Author(s):  
Tuo Shi ◽  
Yuanman Hu ◽  
Miao Liu ◽  
Chunlin Li ◽  
Chuyi Zhang ◽  
...  

With China’s rapid development, urban air pollution problems occur frequently. As one of the principal components of haze, fine particulate matter (PM2.5) has potential negative health effects, causing widespread concern. However, the causal interactions and dynamic relationships between socioeconomic factors and ambient air pollution are still unclear, especially in specific regions. As an important industrial base in Northeast China, Liaoning Province is a representative mode of social and economic development. Panel data including PM2.5 concentration and three socio-economic indicators of Liaoning Province from 2000 to 2015 were built. The data were first-difference stationary and the variables were cointegrated. The Granger causality test was used as the main method to test the causality. In the results, in terms of the causal interactions, economic activities, industrialization and urbanization processes all showed positive long-term impacts on changes of PM2.5 concentration. Economic growth and industrialization also significantly affected the variations in PM2.5 concentration in the short term. In terms of the contributions, industrialization contributed the most to the variations of PM2.5 concentration in the sixteen years, followed by economic growth. Though Liaoning Province, an industry-oriented region, has shown characteristics of economic and industrial transformation, policy makers still need to explore more targeted policies to address the regional air pollution issue.


Author(s):  
Youngrin Kwag ◽  
Min-ho Kim ◽  
Shinhee Ye ◽  
Jongmin Oh ◽  
Gyeyoon Yim ◽  
...  

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.


Author(s):  
Jiyoung Shin ◽  
Jongmin Oh ◽  
In Sook Kang ◽  
Eunhee Ha ◽  
Wook Bum Pyun

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.


2019 ◽  
Vol 25 (6) ◽  
pp. 898-907 ◽  
Author(s):  
M. Gokul Raj ◽  
S. Karthikeyan

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.


2019 ◽  
Vol 8 (3) ◽  
pp. 7922-7927

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.


Author(s):  
Qing Tian ◽  
Mei Li ◽  
Scott Montgomery ◽  
Bo Fang ◽  
Chunfang Wang ◽  
...  

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.


Author(s):  
Daoru Liu ◽  
Qinli Deng ◽  
Zeng Zhou ◽  
Yaolin Lin ◽  
Junwei Tao

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%.


2019 ◽  
Vol 19 (14) ◽  
pp. 9287-9308 ◽  
Author(s):  
Erin E. McDuffie ◽  
Caroline C. Womack ◽  
Dorothy L. Fibiger ◽  
William P. Dube ◽  
Alessandro Franchin ◽  
...  

Abstract. Mountain basins in Northern Utah, including the Salt Lake Valley (SLV), suffer from wintertime air pollution events associated with stagnant atmospheric conditions. During these events, fine particulate matter concentrations (PM2.5) can exceed national ambient air quality standards. Previous studies in the SLV have found that PM2.5 is primarily composed of ammonium nitrate (NH4NO3), formed from the condensation of gas-phase ammonia (NH3) and nitric acid (HNO3). Additional studies in several western basins, including the SLV, have suggested that production of HNO3 from nocturnal heterogeneous N2O5 uptake is the dominant source of NH4NO3 during winter. The rate of this process, however, remains poorly quantified, in part due to limited vertical measurements above the surface, where this chemistry is most active. The 2017 Utah Winter Fine Particulate Study (UWFPS) provided the first aircraft measurements of detailed chemical composition during wintertime pollution events in the SLV. Coupled with ground-based observations, analyses of day- and nighttime research flights confirm that PM2.5 during wintertime pollution events is principally composed of NH4NO3, limited by HNO3. Here, observations and box model analyses assess the contribution of N2O5 uptake to nitrate aerosol during pollution events using the NO3- production rate, N2O5 heterogeneous uptake coefficient (γ(N2O5)), and production yield of ClNO2 (φ(ClNO2)), which had medians of 1.6 µg m−3 h−1, 0.076, and 0.220, respectively. While fit values of γ(N2O5) may be biased high by a potential under-measurement in aerosol surface area, other fit quantities are unaffected. Lastly, additional model simulations suggest nocturnal N2O5 uptake produces between 2.4 and 3.9 µg m−3 of nitrate per day when considering the possible effects of dilution. This nocturnal production is sufficient to account for 52 %–85 % of the daily observed surface-level buildup of aerosol nitrate, though accurate quantification is dependent on modeled dilution, mixing processes, and photochemistry.


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