scholarly journals Spatiotemporal Variations and Factors of Air Quality in Urban Central China during 2013–2015

2019 ◽  
Vol 17 (1) ◽  
pp. 229 ◽  
Author(s):  
Mao Mao ◽  
Xiaolin Zhang ◽  
Yamei Shao ◽  
Yan Yin
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Trace Gases ◽  
Pollution Prevention ◽  
Ambient Air ◽  
Control Measures ◽  
Central China ◽  
World Health ◽  
Haze Pollution ◽  
Grade Ii

Spatiotemporal behaviors of particulate matter (PM2.5 and PM10) and trace gases (SO2, NO2, CO, and O3) in Hefei during the period from December 2013 to November 2015 are investigated. The mean annual PM2.5 (PM10) concentrations are 89.1 ± 59.4 µg/m3 (118.9 ± 66.8 µg/m3) and 61.6 ± 32.2 µg/m3 (91.3 ± 40.9 µg/m3) during 2014 and 2015, respectively, remarkably exceeding the Chinese Ambient Air Quality Standards (CAAQS) grade II. All trace gases basically meet the requirements though NO2 and O3 have a certain upward trend. Old districts have the highest pollution levels, followed by urban periphery sites and new districts. Severe haze pollution occurs in Hefei, with frequent exceedances in particulate matter with 178 (91) days in 2014 (2015). The abnormal PM2.5 concentrations in June 2014 attributed to agricultural biomass burning from moderate resolution imaging spectroradiometry (MODIS) wildfire maps and aerosol optical depth (AOD) analysis. PM2.5 is recognized as the major pollutant, and a longer interspecies relationship is found between PM2.5 and other criteria pollutants for episode days as compared to non-episode days. The air pollution in Hefei tends to be influenced by local primary emissions, secondary formation, and regional transport from adjacent cities and remote regions. Most areas of Anhui, southern Jiangsu, northern Zhejiang, and western Shandong are identified as the common high-potential source regions of PM2.5. Approximately 9.44 and 8.53 thousand premature mortalities are attributed to PM2.5 exposure in 2014 and 2015. The mortality benefits will be 32% (24%), 47% (41%), 70% (67%), and 85% (83%) of the total premature mortalities in 2014 (2015) when PM2.5 concentrations meet the CAAQS grade II, the World Health Organization (WHO) IT-2, IT-3, and Air Quality Guideline, respectively. Hence, joint pollution prevention and control measures need to be strengthened due to pollutant regional diffusion, and much higher health benefits could be achieved as the Hefei government adopts more stringent WHO guidelines for PM2.5.

scholarly journals Effectiveness of SOx, NOx, and Primary Particulate Matter Control Strategies in the Improvement of Ambient PM Concentration in Taiwan

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 460
Author(s):  
Jiun-Horng Tsai ◽  
Ming-Ye Lee ◽  
Hung-Lung Chiang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Model Simulation ◽  
Control Strategies ◽  
Ambient Air ◽  
Clean Air Act ◽  
Control Measures ◽  
Control Plan ◽  
Clean Air ◽  
Pm2.5 Concentration

The Community Multiscale Air Quality (CMAQ) measurement was employed for evaluating the effectiveness of fine particulate matter control strategies in Taiwan. There are three scenarios as follows: (I) the 2014 baseline year emission, (II) 2020 emissions reduced via the Clean Air Act (CAA), and (III) other emissions reduced stringently via the Clean Air Act. Based on the Taiwan Emission Data System (TEDs) 8.1, established in 2014, the emission of particulate matter 2.5 (PM2.5) was 73.5 thousand tons y−1, that of SOx was 121.3 thousand tons y−1, and that of NOx was 404.4 thousand tons y−1 in Taiwan. The CMAQ model simulation indicated that the PM2.5 concentration was 21.9 μg m−3. This could be underestimated by 24% in comparison with data from the ambient air quality monitoring stations of the Taiwan Environmental Protection Administration (TEPA). The results of the simulation of the PM2.5 concentration showed high PM2.5 concentrations in central and southwestern Taiwan, especially in Taichung and Kaohsiung. Compared to scenario I, the average annual concentrations of PM2.5 for scenario II and scenario III showed reductions of 20.1% and 28.8%, respectively. From the results derived from the simulation, it can be seen that control of NOx emissions may improve daily airborne PM2.5 concentrations in Taiwan significantly and control of directly emitted PM2.5 emissions may improve airborne PM2.5 concentrations each month. Nevertheless, the results reveal that the preliminary control plan could not achievethe air quality standard. Therefore, the efficacy and effectiveness of the control measures must be considered to better reduce emissions in the future.

scholarly journals Impact of SARS-CoV-2 on Ambient Air Quality in Northwest China (NWC)

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 518
Author(s):  
Shah Zaib ◽  
Jianjiang Lu ◽  
Muhammad Zeeshaan Shahid ◽  
Sunny Ahmar ◽  
Imran Shahid
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Fine Particulate Matter ◽  
Temporal Distribution ◽  
Ambient Air ◽  
Northwest China ◽  
Ambient Air Quality ◽  
Coarse Particulate Matter ◽  
Air Quality Improvement ◽  
Grade Ii

SARS-CoV-2 was discovered in Wuhan (Hubei) in late 2019 and covered the globe by March 2020. To prevent the spread of the SARS-CoV-2 outbreak, China imposed a countrywide lockdown that significantly improved the air quality. To investigate the collective effect of SARS-CoV-2 on air quality, we analyzed the ambient air quality in five provinces of northwest China (NWC): Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX) and Qinghai (QH), from January 2019 to December 2020. For this purpose, fine particulate matter (PM2.5), coarse particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were obtained from the China National Environmental Monitoring Center (CNEMC). In 2020, PM2.5, PM10, SO2, NO2, CO, and O3 improved by 2.72%, 5.31%, 7.93%, 8.40%, 8.47%, and 2.15%, respectively, as compared with 2019. The PM2.5 failed to comply in SN and XJ; PM10 failed to comply in SN, XJ, and NX with CAAQS Grade II standards (35 µg/m3, 70 µg/m3, annual mean). In a seasonal variation, all the pollutants experienced significant spatial and temporal distribution, e.g., highest in winter and lowest in summer, except O3. Moreover, the average air quality index (AQI) improved by 4.70%, with the highest improvement in SN followed by QH, GS, XJ, and NX. AQI improved in all seasons; significant improvement occurred in winter (December to February) and spring (March to May) when lockdowns, industrial closure etc. were at their peak. The proportion of air quality Class I improved by 32.14%, and the number of days with PM2.5, SO2, and NO2 as primary pollutants decreased while they increased for PM10, CO, and O3 in 2020. This study indicates a significant association between air quality improvement and the prevalence of SARS-CoV-2 in 2020.

scholarly journals Ambient air quality in the Kathmandu Valley, Nepal, during the pre-monsoon: concentrations and sources of particulate matter and trace gases

2020 ◽  
Vol 20 (5) ◽  
pp. 2927-2951 ◽  
Author(s):  
Md. Robiul Islam ◽  
Thilina Jayarathne ◽  
Isobel J. Simpson ◽  
Benjamin Werden ◽  
John Maben ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Organic Carbon ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Trace Gases ◽  
Ambient Air ◽  
Kathmandu Valley ◽  
Ambient Air Quality ◽  
Regional Air Quality

Abstract. The Kathmandu Valley in Nepal is a bowl-shaped urban basin that experiences severe air pollution that poses health risks to its 3.5 million inhabitants. As part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE), ambient air quality in the Kathmandu Valley was investigated from 11 to 24 April 2015, during the pre-monsoon season. Ambient concentrations of fine and coarse particulate matter (PM2.5 and PM10, respectively), online PM1, inorganic trace gases (NH3, HNO3, SO2, and HCl), and carbon-containing gases (CO2, CO, CH4, and 93 non-methane volatile organic compounds; NMVOCs) were quantified at a semi-urban location near the center of the valley. Concentrations and ratios of NMVOC indicated origins primarily from poorly maintained vehicle emissions, biomass burning, and solvent/gasoline evaporation. During those 2 weeks, daily average PM2.5 concentrations ranged from 30 to 207 µg m−3, which exceeded the World Health Organization 24 h guideline by factors of 1.2 to 8.3. On average, the non-water mass of PM2.5 was composed of organic matter (48 %), elemental carbon (13 %), sulfate (16 %), nitrate (4 %), ammonium (9 %), chloride (2 %), calcium (1 %), magnesium (0.05 %), and potassium (1 %). Large diurnal variability in temperature and relative humidity drove corresponding variability in aerosol liquid water content, the gas–aerosol phase partitioning of NH3, HNO3, and HCl, and aerosol solution pH. The observed levels of gas-phase halogens suggest that multiphase halogen-radical chemistry involving both Cl and Br impacted regional air quality. To gain insight into the origins of organic carbon (OC), molecular markers for primary and secondary sources were quantified. Levoglucosan (averaging 1230±1154 ng m−3), 1,3,5-triphenylbenzene (0.8±0.6 ng m−3), cholesterol (2.9±6.6 ng m−3), stigmastanol (1.0 ±0.8 ng m−3), and cis-pinonic acid (4.5±1.9 ng m−3) indicate contributions from biomass burning, garbage burning, food cooking, cow dung burning, and monoterpene secondary organic aerosol, respectively. Drawing on source profiles developed in NAMaSTE, chemical mass balance (CMB) source apportionment modeling was used to estimate contributions to OC from major primary sources including garbage burning (18±5 %), biomass burning (17±10 %) inclusive of open burning and biomass-fueled cooking stoves, and internal-combustion (gasoline and diesel) engines (18±9 %). Model sensitivity tests with newly developed source profiles indicated contributions from biomass burning within a factor of 2 of previous estimates but greater contributions from garbage burning (up to three times), indicating large potential impacts of garbage burning on regional air quality and the need for further evaluation of this source. Contributions of secondary organic carbon (SOC) to PM2.5 OC included those originating from anthropogenic precursors such as naphthalene (10±4 %) and methylnaphthalene (0.3±0.1 %) and biogenic precursors for monoterpenes (0.13±0.07 %) and sesquiterpenes (5±2 %). An average of 25 % of the PM2.5 OC was unapportioned, indicating the presence of additional sources (e.g., evaporative and/or industrial emissions such as brick kilns, food cooking, and other types of SOC) and/or underestimation of the contributions from the identified source types. The source apportionment results indicate that anthropogenic combustion sources (including biomass burning, garbage burning, and fossil fuel combustion) were the greatest contributors to PM2.5 and, as such, should be considered primary targets for controlling ambient PM pollution.

scholarly journals Ambient air quality in the Kathmandu Valley, Nepal during the pre-monsoon: Concentrations and sources of particulate matter and trace gases

2019 ◽  
Author(s):  
Md. Robiul Islam ◽  
Thilina Jayarathne ◽  
Isobel J. Simpson ◽  
Benjamin Werden ◽  
John Maben ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Organic Carbon ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Trace Gases ◽  
Ambient Air ◽  
Kathmandu Valley ◽  
Ambient Air Quality ◽  
Regional Air Quality

Abstract. The Kathmandu Valley in Nepal is a bowl-shaped urban basin that experiences severe air pollution that poses health risks to its 3.5 million inhabitants. As part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE), ambient air quality in the Kathmandu Valley was investigated from 11 to 24 April 2015, during the pre-monsoon season. Ambient concentrations of fine and coarse particulate matter (PM2.5 and PM10, respectively), online PM1, inorganic trace gases (NH3, HNO3, SO2, and HCl), and carbon-containing gases (CO2, CO, CH4, and 85 non-methane volatile organic compounds; NMVOC) were quantified at a semi-urban location near the center of the valley. Concentrations and ratios of NMVOC indicated that origins primarily from poorly-maintained vehicle emissions, biomass burning, and solvent/gasoline evaporation. During those two weeks, daily average PM2.5 concentrations ranged from 30 to 207 µg m−3, which exceeded the World Health Organization 24 hour guideline by factors of 1.2 to 8.3. On average, the non-water mass of PM2.5 was composed of organic matter (48 %), elemental carbon (13 %), sulfate (16 %), nitrate (4 %), ammonium (9 %), chloride (2 %), calcium (1 %), magnesium (0.05 %), and potassium (1 %). Large diurnal variability in temperature and relative humidity drove corresponding variability in aerosol liquid water content, the gas-aerosol phase partitioning of NH3, HNO3, and HCl, and aerosol solution pH. The observed levels of gas-phase halogens suggest that multiphase halogen-radical chemistry involving both Cl and Br impacted regional air quality. To gain insight into the origins of organic carbon (OC), molecular markers for primary and secondary sources were quantified. Levoglucosan (1230 ± 1153 ng m−3), 1,3,5-triphenylbenzene (0.8 ±0.5 ng m−3), cholesterol (3.0 ± 6.7 ng m−3), stigmastanol (1.4 ± 6.7 ng m−3), and cis-pinonic acid (4.5 ± 0.6 ng m−3) indicate contributions from biomass burning, garbage burning, food cooking, cow-dung burning, and monoterpene secondary organic aerosol, respectively. Drawing on source profiles developed in NAMaSTE, chemical mass balance (CMB) source apportionment modeling was used to estimate contributions to OC from major primary sources including garbage burning (18 ± 5 %), biomass burning (17 ± 10 %) inclusive of open burning and biomass-fueled cooking stoves, and internal-combustion (gasoline and diesel) engines (18 ± 9 %). Model sensitivity tests with newly-developed source profiles indicated contributions from biomass burning within a factor of two of previous estimates, but relatively greater contributions from garbage burning (up to three times), indicating large potential impacts of garbage burning on regional air quality and the need for further evaluation of this source. Contributions of secondary organic carbon (SOC) to PM2.5 OC included those originating from anthropogenic precursors for naphthalene (10 ± 4 %) and methylnaphthalene (0.3 ± 0.1 %) and biogenic precursors for monoterpenes (0.13 ± 0.07 %) and sesquiterpenes (5 ± 2 %). An average of 25 % of the PM2.5 OC was unapportioned, indicating the presence of additional sources (e.g., evaporative and/or industrial emissions such as brick kilns, food cooking, and other types of SOC) or underestimation of the contributions from the identified source types. The source apportionment results indicate that anthropogenic combustion sources (including biomass burning, garbage burning, and fossil-fuel combustion) were the greatest contributors to PM2.5 and, as such, should be considered primary targets for controlling ambient PM pollution.

scholarly journals Health Implications of Air Quality Index of Fine and Coarse Particulates During Outdoor Combustion of Biomass in the Niger Delta, Nigeria

2021 ◽  
pp. 21-26
Author(s):  
Glory Richard ◽  
Wisdom Ebiye Sawyer ◽  
Sylvester Chibueze Izah
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Niger Delta ◽  
Quality Index ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Air Quality Index ◽  
World Health ◽  
Health Implications ◽  
Pm2.5 And Pm10

Rural dwellers in the Niger Delta commonly use biomass for cooking and other activities. This study investigated the air quality index of fine particulate matter 2.5 (PM2.5) and coarse particulate matter 10 (PM10) and its health implications during outdoor combustion of fuelwood in the Niger Delta, Nigeria. A mini-volume air sampler (model: AEROCET 531) was used to measure PM2.5, PM10, and total suspended particulate (TSP) in the study area. A bimonthly triplicate sampling was carried out at 3 distances in 4 different states spanning one Calendar year. The results showed that PM2.5, PM10, and TSP ranged from 19.85 – 27.95µg/m3, 55.66 – 80.59µg/m3, and 74.29 – 140.44µg/m3, respectively. There was statistical variation across the different months, locations and distances, and their interactions. The concentration of PM2.5 and PM10 occasionally exceeds the World Health Organization limits of 25µg/m3 and 50µg/m3 for 24-hourly average, respectively. The air quality index showed no contamination to slight contamination in both seasons. The air quality index indicates that the air is slightly contaminated at the emission source which decreased as distance away increased. Therefore, there is a need for the regulatory agencies to consider PM2.5 and PM10 in the monitoring of ambient air quality to forestall potential hazards associated with human exposure.

scholarly journals The impact of measures to reduce ambient air PM<sub>10</sub> concentrations originating from road dust, evaluated for a street canyon in Helsinki

2019 ◽  
Vol 19 (17) ◽  
pp. 11199-11212 ◽  
Author(s):  
Ana Stojiljkovic ◽  
Mari Kauhaniemi ◽  
Jaakko Kukkonen ◽  
Kaarle Kupiainen ◽  
Ari Karppinen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Street Canyon ◽  
Dust Emission ◽  
Road Dust ◽  
Ambient Air ◽  
Air Quality Measurements ◽  
Emission Models ◽  
The Impact ◽  
Quality Measurements

Abstract. We have numerically evaluated how effective selected potential measures would be for reducing the impact of road dust on ambient air particulate matter (PM10). The selected measures included a reduction of the use of studded tyres on light-duty vehicles and a reduction of the use of salt or sand for traction control. We have evaluated these measures for a street canyon located in central Helsinki for four years (2007–2009 and 2014). Air quality measurements were conducted in the street canyon for two years, 2009 and 2014. Two road dust emission models, NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and FORE (Forecasting Of Road dust Emissions), were applied in combination with the Operational Street Pollution Model (OSPM), a street canyon dispersion model, to compute the street increments of PM10 (i.e. the fraction of PM10 concentration originating from traffic emissions at the street level) within the street canyon. The predicted concentrations were compared with the air quality measurements. Both road dust emission models reproduced the seasonal variability of the PM10 concentrations fairly well but under-predicted the annual mean values. It was found that the largest reductions of concentrations could potentially be achieved by reducing the fraction of vehicles that use studded tyres. For instance, a 30 % decrease in the number of vehicles using studded tyres would result in an average decrease in the non-exhaust street increment of PM10 from 10 % to 22 %, depending on the model used and the year considered. Modelled contributions of traction sand and salt to the annual mean non-exhaust street increment of PM10 ranged from 4 % to 20 % for the traction sand and from 0.1 % to 4 % for the traction salt. The results presented here can be used to support the development of optimal strategies for reducing high springtime particulate matter concentrations originating from road dust.

scholarly journals Assessment of Emission Reduction and Meteorological Change in PM2.5 and Transport Flux in Typical Cities Cluster during 2013–2017

2021 ◽  
Vol 13 (10) ◽  
pp. 5685
Author(s):  
Panbo Guan ◽  
Hanyu Zhang ◽  
Zhida Zhang ◽  
Haoyuan Chen ◽  
Weichao Bai ◽  
...  
Keyword(s):  
Air Quality ◽  
Action Plan ◽  
Influence Factors ◽  
Pollution Prevention ◽  
Weather Conditions ◽  
Yangtze River Delta ◽  
Control Measures ◽  
Joint Control ◽  
Air Quality Model ◽  
Quality Model

Under the Air Pollution Prevention and Control Action Plan (APPCAP) implemented, China has witnessed an air quality change during the past five years, yet the main influence factors remain relatively unexplored. Taking the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions as typical cluster cities, the Weather Research Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were introduced to demonstrate the meteorological and emission contribution and PM2.5 flux distribution. The results showed that the PM2.5 concentration in BTH and YRD significantly declined with a descend ratio of −39.6% and −28.1%, respectively. For the meteorological contribution, those regions had a similar tendency with unfavorable conditions in 2013–2015 (contribution concentration 1.6–3.8 μg/m3 and 1.1–3.6 μg/m3) and favorable in 2016 (contribution concentration −1.5 μg/m3 and −0.2 μg/m3). Further, the absolute value of the net flux’s intensity was positively correlated with the degree of the favorable/unfavorable weather conditions. When it came to emission intensity, the total net inflow flux increased, and the outflow flux decreased significantly across the border with the emission increasing. In short: the aforementioned results confirmed the effectiveness of the regional joint emission control and provided scientific support for the proposed effective joint control measures.

scholarly journals Ambient Particulate Matter Air Pollution in Mpererwe District, Kampala, Uganda: A Pilot Study

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Stephan Schwander ◽  
Clement D. Okello ◽  
Juergen Freers ◽  
Judith C. Chow ◽  
John G. Watson ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Pilot Study ◽  
Fine Particles ◽  
Airborne Particulate Matter ◽  
Personal Exposure ◽  
Ambient Air ◽  
Combustion Products ◽  
Carbonaceous Aerosol ◽  
Coarse Particles

Air quality in Kampala, the capital of Uganda, has deteriorated significantly in the past two decades. We made spot measurements in Mpererwe district for airborne particulate matter PM2.5(fine particles) and coarse particles. PM was collected on Teflon-membrane filters and analyzed for mass, 51 elements, 3 anions, and 5 cations. Both fine and coarse particle concentrations were above 100 µg/m3in all the samples collected. Markers for crustal/soil (e.g., Si and Al) were the most abundant in the PM2.5fraction, followed by primary combustion products from biomass burning and incinerator emissions (e.g., K and Cl). Over 90% of the measured PM2.5mass can be explained by crustal species (41% and 59%) and carbonaceous aerosol (33%–55%). Crustal elements dominated the coarse particles collected from Kampala. The results of this pilot study are indicative of unhealthy air and suggest that exposure to ambient air in Kampala may increase the burden of environmentally induced cardiovascular, metabolic, and respiratory diseases including infections. Greater awareness and more extensive research are required to confirm our findings, to identify personal exposure and pollution sources, and to develop air quality management plans and policies to protect public health.

scholarly journals Poor Air Quality and Its Association with Mortality in Ho Chi Minh City: Case Study

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 750
Author(s):  
Hoang Ngoc Khue Vu ◽  
Quang Phuc Ha ◽  
Duc Hiep Nguyen ◽  
Thi Thu Thuy Nguyen ◽  
Thoai Tam Nguyen ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Air Pollutants ◽  
Ambient Air ◽  
Air Quality Modeling ◽  
World Health ◽  
Ho Chi Minh City ◽  
Annual Average ◽  
Quality Modeling ◽  
Concentration Of Air Pollutants

Along with its rapid urban development, Ho Chi Minh City (HCMC) in recent years has suffered a high concentration of air pollutants, especially fine particulate matters or PM2.5. A comprehensive study is required to evaluate the air quality conditions and their health impact in this city. Given the lack of adequate air quality monitoring data over a large area of the size of HCMC, an air quality modeling methodology is adopted to address the requirement. Here, by utilizing a corresponding emission inventory in combination with The Air Pollution Model-Chemical Transport Model (TAPM-CTM), the predicted concentration of air pollutants is first obtained for PM2.5, NOx, and SO2. Then by associating the pollutants exposed with the mortality rate from three causes, namely Ischemic Heart Disease (IHD), cardiopulmonary, and lung cancer, the impact of air pollution on human health is obtained for this purpose. Spatial distribution has shown a high amount of pollutants concentrated in the central city with a high density of combustion vehicles (motorcycles and automobiles). In addition, a significant amount of emissions can be observed from stevedoring and harbor activities, including ferries and cargo handling equipment located along the river. Other sources such as household activities also contribute to an even distribution of emission across the city. The results of air quality modeling showed that the annual average concentrations of NO2 were higher than the standard of Vietnam National Technical Regulation on Ambient Air Quality (QCVN 05: 2013 40 µg/m3) and World Health Organization (WHO) (40 µg/m3). The annual average concentrations of PM2.5 were 23 µg/m3 and were also much higher than the WHO (10 µg/m3) standard by about 2.3 times. In terms of public health impacts, PM2.5 was found to be responsible for about 1136 deaths, while the number of mortalities from exposure to NO2 and SO2 was 172 and 89 deaths, respectively. These figures demand some stringent measures from the authorities to potentially remedy the alarming situation of air pollution in HCM City.

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