Current Status of Fine Particulate Matter (PM2.5) in Vietnam’s Most Populous City, Ho Chi Minh City

Hiền, Tô Thị; Thien, Nguyen Doan; Nguyen, Nguyen Thao; Vinh, Le Xuan; Takenaka, Norimichi; Huy, Dương Hữu

doi:10.4209/aaqr.2018.12.0471

Cited by 68 publications

(39 citation statements)

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“…Southeast Asia (SEA; here defined as Singapore, Indonesia, Philippines, Malaysia, Thailand, Vietnam, Myanmar, Brunei, Cambodia, and Laos), a well-known region for its high pollution loadings and complex meteorology (Lin et al, 2013;Salinas et al, 2013;Tsay et al, 2016;Kusumaningtyas et al, 2018;Khamkaew et al, 2016;Pani et al, 2016aPani et al, , 2016bPani et al, , 2018Pani et al, , 2019aPani et al, , 2019bPani et al, , 2020Hien et al, 2019;Tham et al, 2019;Dahari et al, 2020), has been hit hard by the COVID-19 pandemic with a surge of new cases recently (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

Association of COVID-19 pandemic with meteorological parameters over Singapore

Pani

Lin

Babu

2020

Science of The Total Environment

218

246

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Section: Introductionmentioning

confidence: 99%

Association of COVID-19 pandemic with meteorological parameters over Singapore

Pani

Lin

Babu

2020

Science of The Total Environment

218

246

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“…; to study the trend and characteristics of PM 2.5 ( Chen et al, 2020 ; Fontes et al, 2017 ; Sreekanth et al, 2018 ; Liang et al, 2016 ; Batterman et al, 2016 ; San Martini et al, 2015 ), to compare with other data and model evaluation ( Jiang et al, 2015 ; Li, 2020 ; Matthias et al, 2017 ; Mukherjee and Toohey, 2016 ; Shimadera et al, 2016 ; Uno et al, 2014 ; Wang et al, 2018 ), and to estimate the health impacts ( Han et al, 2020 ; Lowsen and Conway, 2016 ; Luong et al, 2020 ; Nhung et al, 2020 ; Tian et al, 2020 ; Wang et al, 2020 ; You et al, 2016 ; Zhang et al, 2020 ). While most of the studies are carried out in China, few studies have been carried out for other countries including Vietnam ( Hien et al, 2019 ; Luong et al, 2020 ), Japan ( Shimadera et al, 2016 ) Indonesia ( Kusuma et al, 2019 ), Mongolia ( Hill et al, 2017 ), Bangladesh ( Auvee and Bashar, 2019 ), and Singapore ( Liu and Salvo, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Exceedances and trends of particulate matter (PM2.5) in five Indian megacities

Singh

Biswal

2021

Science of The Total Environment

120

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Fine particulate matter (PM 2.5 ) is the leading environmental risk factor that requires regular monitoring and analysis for effective air quality management. This work presents the variability, trend, and exceedance analysis of PM 2.5 measured at US Embassy and Consulate in five Indian megacities (Chennai, Kolkata, Hyderabad, Mumbai, and New Delhi) for six years (2014–2019). Among all cities, Delhi is found to be the most polluted city followed by Kolkata, Mumbai, Hyderabad, and Chennai. The trend analysis for six years for five megacities suggests a statistically significant decreasing trend ranging from 1.5 to 4.19 μg/m 3 (2%–8%) per year. Distinct diurnal, seasonal, and monthly variations are observed in the five cities due to the different site locations and local meteorology. All cities show the highest and lowest concentrations in the winter and monsoon months respectively except for Chennai which observed the lowest levels in April. All the cities consistently show morning peaks (~08: 00–10:00 h) and the lowest level in late afternoon hours (~15:00–16:00 h). We found that the PM 2.5 levels in the cities exceed WHO standards and Indian NAAQS for 50% and 33% of days in a year except for Chennai. Delhi is found to have more than 200 days of exceedances in a year and experiences an average 15 number of episodes per year when the level exceeds the Indian NAAQS. The trends in the exceedance with a varying threshold (20–380 μg/m 3 ) suggest that not only is the annual mean PM 2.5 decreasing in Delhi but also the number of exceedances is decreasing. This decrease can be attributed to the recent policies and regulations implemented in Delhi and other cities for the abatement of air pollution. However, stricter compliance of the National Clean Air Program (NCAP) policies can further accelerate the reduction of the pollution levels.

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“…Most PM occurs naturally in the environment, but increasing anthropogenic interferences in the environment have significantly increased the PM burden (Cha et al, 2019). Anthropogenic sources of PM include vehicular emissions and activities such as biomass burning, industrial processing, agricultural operations, and construction activities (Fang et al, 2017;Widiana et al, 2017;Deshmukh et al, 2019;Hao et al, 2019;Hien et al, 2019;Hu et al, 2019;Liu et al, 2019;Shahid et al, 2019). PM emitted from natural sources and human activities includes carbon monoxide (CO), nitrogen dioxide (NO 2 ) and sulfur dioxide (SO 2 ).…”

Section: Introductionmentioning

confidence: 99%

Air Pollution Levels Related to Peak Expiratory Flow Rates among Adult Asthmatics in Lampang, Thailand

Chujit

Wiwatanadate

Deesomchok

et al. 2020

Aerosol Air Qual. Res.

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Asthmatics may suffer harmful health effects from air pollution. This year-long study, which was conducted from November 2015 till October 2016 and resulted in 12,045 data points from 33 participants, assessed the relationships (with a 95% confidence interval [CI]) between measured air pollutant (CO, NO 2 , O 3 , SO 2 , PM 2.5 and PM 10) concentrations and peak expiratory flow rates (PEFRs) among adults with asthma in the district of Mae Moh in Lampang, Thailand. A positive correlation was found between the mean daily concentration of NO 2 from 4 days prior ("lag 4") and the PEFR upon waking ("morning PEFR"), with an increase of 1 ppb in the former being associated with an increase of 1.34 L min-1 (95% CI: 0.25, 2.44) in the latter. Also, the interaction between NO 2 (lag 4) and PM 10 (lag 6) was multiplicatively associated with a decrease of-0.015 L min-1 in the morning PEFR, which was also negatively associated with the maximum daily concentration ("max") of NO 2 (lag 2) and that of PM 10 (lag 6), with coefficients of-0.07 and-0.013, respectively. Furthermore, when including PM 2.5 max in the generalized estimating equation model, only NO 2 max (lag 2) and CO max (lag 6) were negatively associated with the morning PEFR, displaying coefficients of-0.08 and-1.71, respectively. O 3 max (lag 3) and PM 2.5 max exhibited positive relationships with the PEFR before sleeping ("evening PEFR"), with coefficients of 0.078 and 0.029, respectively. Additionally, the average daily PEFR was positively associated with the average daily concentration of NO 2 (lag 4), with a coefficient of 0.15, but negatively associated with that of SO 2 , with a coefficient of-0.47. We also observed a negative relationship between the average daily PEFR and NO 2 max (lag 2), with a coefficient of-0.05, but a positive one between the former and O 3 max (lag 3), with a coefficient of 0.06. Our results indicate that the delayed-and, in some cases, negative-effects of these pollutants on PEFRs must be considered in health forecasting and that preventative measures should be implemented to control certain emissions at the source.

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Current Status of Fine Particulate Matter (PM2.5) in Vietnam’s Most Populous City, Ho Chi Minh City

Cited by 68 publications

References 0 publications

Association of COVID-19 pandemic with meteorological parameters over Singapore

Association of COVID-19 pandemic with meteorological parameters over Singapore

Exceedances and trends of particulate matter (PM2.5) in five Indian megacities

Air Pollution Levels Related to Peak Expiratory Flow Rates among Adult Asthmatics in Lampang, Thailand

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