Sustainable Environment Research xxx (2017) 1e8 Contents lists available at ScienceDirect Sustainable Environment Research journal homepage: www.journals.elsevier.com/sustainableenvironment-research/ Original Research Article Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health Bang Quoc Ho Department of Air Pollution and Climate Change, Institute of Environment & Resources, Vietnam National University, Ho Chi Minh City 0084, Viet Nam a r t i c l e i n f o a b s t r a c t Article history: Received April 2016 Received in revised form 10 August 2016 Accepted 12 October 2016 Available online xxx According to World Health Organization (WHO) and Global Burden of Disease, ambient air pollution is estimated to be responsible for 3.7 million premature deaths in 2012 [1] Therefore, it is urgent to estimate the impact of air pollution on public health and economic damage The objectives of this research are: study the distribution of PM10 concentration over Ho Chi Minh city (HCMC) and relationship to public health and for proposing solutions of diseases prevention in HCM, Vietnam EMIssion SENSitivity model was applied to conduct air emission inventory for transportation sector Then, Finite Volume Model and Transport and Photochemistry Mesoscale Model were used to simulate the meteorology and the spatial distribution of PM10 in HCMC Together with disease data obtained, the US Environmental Benefits Mapping and Analysis Model was applied for calculating the number of deaths and estimating economic losses due to PM10 pollution Finally, solutions to reduce PM10 pollution and protect public health are proposed The results showed that the highest 1-h average concentration of PM10 is 240 mg mÀ3 in North Eastern of HCMC The concentration of PM10 for annual average in District ranged from 17 to 49 mg mÀ3 There are 12 wards of District with PM10 concentration exceeding the WHO guidelines (20 mg mÀ3 for annual average of PM10 and 50 mg mÀ3 for 24-h average) The high concentration of PM10 causes deaths yrÀ1 in District and 204 deaths yrÀ1 in HCMC, and it causes economic losses of 1.84 billion of USD © 2017 Chinese Institute of Environmental Engineering, Taiwan Production and hosting by Elsevier B.V This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/) Keywords: Air pollution Health effects Mortality Ho Chi Minh City Introduction Ho Chi Minh City (HCMC) is the most dynamic area as a social, cultural and economic center of Vietnam District located at South of HCMC, has an area of 4.27 km2 with population of 176,890 people and density of 41,426 person kmÀ2 It is one of the most density areas with energetic economic activities Services, exchange of goods and traffic in this area have been expanded for a long time which drive economic growth Consequently, environment has become polluted, and the citizens have to face many environmental problems Especially in traffic jam conditions, air quality becomes worse which directly affects people's health In a recent study of relationship between air pollution and human health, over 90% children less than years old in HCMC were infected to respiratory disease [2] According to World Economic Forum in 2012, Vietnam E-mail address: bangquoc@yahoo.com Peer review under responsibility of Chinese Institute of Environmental Engineering is one of 10 countries which has the worst air pollution in worldwide [3] and in urban area as HCMC, traffic is the major contributor to air pollution [4] Pollutants emitted from these sources is considered as hazardous pollutants by US Environmental Protection Agency (USEPA), especially particulate matter PM2.5 is believed to cause respiratory disease, lung cancer and mortality In 2012, International Agency for Research on Cancer (IARC) has classified diesel engine emission to Group Carcinogenic to humans [1] The IARC also reported that emissions from diesel engines from trucks, cars, train or boat were one of the major cause of lung and bladder cancer For those reasons, this study was conducted to clarify the relationship between PM10 concentration and mortality in HCMC especially in District and estimate the economic losses Many studies related to air quality management in HCMC have been done recently, including “Air pollution forecast for Ho Chi Minh City, Vietnam in 2015 and 2020” [4] to simulate pollutants over HCMC (NOx, CO, SO2, O3, but not PM10); “Optimal Methodology to Generate Road Traffic Emissions for Air Quality Modeling: Application to Ho Chi Minh City” [5] focusing on air emission for http://dx.doi.org/10.1016/j.serj.2017.01.001 2468-2039/© 2017 Chinese Institute of Environmental Engineering, Taiwan Production and hosting by Elsevier B.V This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 B.Q Ho / Sustainable Environment Research xxx (2017) 1e8 road transportation for Optimal Methodology to Generate Road Traffic Emissions for Air Quality Modeling: Application to Ho Chi Minh City; and “Estimation of Road Traffic Emission Factors from a Long Term Tracer Study” focusing on calculating air emission factor for volatile organic compounds and NOx The previous researches have not focused on PM10 and there is no impact study of PM10 on human health conducted in Vietnam Method and data 2.1 Method In general, the method of this study is described in Fig First, all information on traffic, industrial activities and household's fuel consumption data were collected for calculation of PM10 emission inventory Then FVM (Finite Volume Model) e a meteorology model and TAPOM (Transport and Photochemistry Mesoscale Model) - a dispersion model were applied to make spatial concentration distribution of PM10 Based on WHO guideline for PM10 (20 mg mÀ3 for annual mean), areas with PM10 concentration exceeding WHO guideline were made Finally, applying theory of the Environmental Benefits Mapping and Analysis Program (BenMAP), a GIS computer program developed by USEPA to simulate impact of air pollution change to human health and economic losses and to estimate the mortality cause by PM10 in study area 2.2 Data for PM10 emission inventory The PM10 emission inventory was carried out for HCMC for the year of 2012 2.2.1 Traffic source EMISENS (EMIssion SENSitivity model) model was used to calculate emissions of PM10 from traffic; the model combined two approaches of Bottom-up and Top-down This model is appropriate for developing countries as Vietnam with lack of information Traffic data were collected from survey for road type, vehicle shares, vehicle age, annual daily traffic, etc which was from previous study for calculating traffic emission for HCMC conducted by the author [4] 2.2.2 Industrial source For industrial sources/point sources, PM10 was estimated from 282 major sources (such as Iron, Steel, Cokes, Refinery, and Cement, among others) in boilers, chimneys, generators, etc in HCMC Activity data for each source were collected as fuel consumption, fuel Fig Research flow chart Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 B.Q Ho / Sustainable Environment Research xxx (2017) 1e8 type, treatment methods, etc The small industrial sources using charcoal emit few emissions and were estimated in area source Main information required is fuel consumption for each source and also conducted in study from stationary emission sources of Ho Chi Minh Environmental Protection Agency (HEPA)/HCMC DoNRE (Department of Natural Resources and Environment) [5,6] Table shows emission factor for PM10 by vehicle type from various reference sources [7e9] PM10 for industrial sources was estimated (Eq (1)) using the emission factors shown in Table Gi ¼ XÀ Á K j  Nj (1) À1 where Gi is PM10 emission (kg d ); Ki is emission factor of fuel (kg kgÀ1 or kg mÀ1); and Nj fuel consumption of type j (kg dÀ1 or m3 dÀ1) 2.2.3 Area sources PM10 generating from area sources are household activities and small restaurants from fuel combustion (gases, LPG, charcoal, and firewood) To estimate PM10 emission, we used Eq (2) and emission factors from Table E ¼ ei  P Table Emission factor for PM10 by vehicle type Type Emission factor (g kmÀ1vehicleÀ1) Heavy duty vehicle (HDV) Light duty vehicle (LDV) Bus Car Motorcycle 236* 1.6 236* 0.07 0.2 *Source: [7e9] Table PM10 emission factors for in industrial sources Fuel type DO FO Charcoal Firewood PM10 emission factor (g kgÀ1) Specific weight (kg LÀ1) 0.00063* 0.87 0.00075* 0.96 0.00693* e 0.0036* e *Source: [10], note: “DO is Diesel Oil, FO is Fuel Oil” Table Emission rate of PM10 per person for area sources Fuel Consumption rate (GJ personÀ1 yrÀ1) Emission factor of PM10 (g GJÀ1) Emission rate of PM10 (kg personÀ1 yrÀ1) Gas Charcoal 3.5 3.5 3.7 695 0.013 2.433 (2) where E is emission of pollutant i (kgi dÀ1), ei emission rate of pollutant i (kgi dÀ1 personÀ1), and P population (person) In addition, according to WHO, fuel consumption rate in urban area is 3.5 GJ personÀ1 yrÀ1 (with gas and charcoal) and in rural 11.7 GJ personÀ1 yrÀ1 (with charcoal and firewood) While PM10 emissions from gas is 3.7 g GJÀ1 and from charcoal is 695 g GJÀ1 and population in District is 176,890 persons The emission rate per person for area source is described in Table 2.3 Using BenMAP to estimate mortality rate Disease data were collected in District since this is the area which has the high population density and economic growth Surveys were conducted over 15 wards of District with total of 200 households (average number of persons in a house is 4.5), collecting data for the averaged exposure time to PM10 and number of death related to respiratory system and strokes The number of interviews corresponds with population distribution and population density; Ward has the highest population with 21,913 people, density of 43,960 persons kmÀ2 and the number of interviews is 25, while ward 14 only has 1781 persons, being the lowest population and accounting for only interviews The equation used for calculating the number of mortality related to air pollutant concentration is as follows: Source: [6] mortality study was conducted by USEPA in North Carolina, USA, dealing with human from European, Africans and Asian in various ages For the present study, baseline mortality of 0.00075 was used when PM10 increases mg mÀ3 comparing with WHO guideline, which means that annually there are 7.5 death in 10,000 people when annual average concentration of PM10 increases by mg mÀ3 Percentage of death in area is percentage of death related to respiratory and cardio in total death in study area Number of exposed (person) is the population in study area Only PM10 concentration was applied in Eq (3) In the study domain, the concentration of PM10 for annual average in District ranged from 17 to 49 mg mÀ3 There are 12 wards of District with PM10 concentration exceeding the WHO guidelines Results and discussion 3.1 Result of emission inventory Table demonstrates the sharing of emission sources, in which major source is traffic with proportion more than 83% Meanwhile, À1 Number of mortality ¼ Air pollution level of pollutant i mg mÀ3  Baseline mortality for air pollutant i mg mÀ3  Percentage of death in area ðfor a yearÞ Â Number of exposed ðpersonÞ Where: Air pollution level of pollutant i (mg mÀ3): is the value of PM10 concentration in study area higher than WHO guideline for pollutant i; or the different concentration of different scenario In this study, annual average concentration is for PM10 and compare with WHO guideline (20 mg mÀ3) Baseline mortality for air pollutant i (mg mÀ3)À1 is mortality change when pollutant i increase or decrease in air quality The (3) EMISENS model also shows (i) generating mostly from hot emission stage with 98% total amount of traffic source, and (ii) HDV and motorcycle are two main contributors 3.2 Uncertain analysis for air emission inventory Uncertainty is one of the main issues in the development of an emission inventory In this study, there are many parameters which Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 B.Q Ho / Sustainable Environment Research xxx (2017) 1e8 Table Result of PM10 emission inventory for HCMC and district Source PM10 emission for Percentage PM10 emission for Percentage HCMC (ton yrÀ1) district (ton yrÀ1) (%) (%) Traffic Industry Household activities Total 34,440 3880 2930 83.5 9.4 7.1 292 24 67 76.4 6.2 17.4 41,250 100 382 100 can be affected by the uncertainties of the results of the emission inventory A discussion of those uncertainties follows: Most of the emission factors for this inventory were derived from EMEP/EEA Air Pollution Emission Inventory Guidebook (2009), updated in 2013, while some emission factors were obtained from other literature sources It should be noted the availability of local emission factors for Vietnam was very limited The completeness of data from field surveys is not always consistent as interviews may vary from source to source Sometimes the data obtained were from verbal communication with the authorities or company officers There was a lack of official data from local agencies, especially for industrial data Although the emission inventory group put effort into including all potential sources into the inventory, there might be some sources missing and this could potentially underestimate the total emissions Air emissions from burning pesticide's plastic bag were not included in this inventory due to the lack of available information although there are few plants Some investigations on these sources are needed in the future There was a lack of traffic information on the side streets, which is one of the key features of road transport in the study domain Many potential particulate emission sources are omitted For example, uncontrolled biomass burning, unpaved roads and other natural sources 3.3 Spatial distribution of PM10 After calculating emission of PM10, MapInfo software was used to make PM10 spatial distribution map with grid cell km2 (1  km), domain with 34  30 cell for x and y direction PM10 emissions in each cell are the input data for TAPOM This domain is for PM10 distribution in HCMC area and for air quality modeling, and then extract the final result of PM10 concentration map For industrial sources, emissions of PM10 are distributed depending on location of plants and factories In Fig the green spots stand for plants and color in each cell show the amount emission of PM10 (g hÀ1 kmÀ2) Therefore, the greener spots the more emissions of PM10 Result shows that PM10 emission range from to 1.27 g hÀ1 kmÀ2 Distribution of PM10 for area sources is showed in Fig which is based on population density The result of PM10 emission ranged from to 2.02 g hÀ1 kmÀ2 For traffic sources, emissions of PM10 distribution are based on road length in each cell Therefore, the higher traffic density, the more emission of PM10 Fig demonstrates emission load of PM10 ranging from to 1.84 g hÀ1 kmÀ2 Meteorology model FVM used data from National Center for Environment Prediction and US Geological Survey for boundary and initial condition (temperature, geopotential height, wind speed, etc.) as well as land data and Fig Location of industrial sources (green circle) and spatial distribution of PM10 for industrial source (different color is emission load of PM10 in g hÀ1 kmÀ2) in HCMC; the bold black line is the location map of HCMC Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 B.Q Ho / Sustainable Environment Research xxx (2017) 1e8 Fig Spatial distribution of PM10 for household activities source (different color is emission load of PM10 in g hÀ1 kmÀ2) in HCMC; the bold black line is the location map of HCMC Fig Road traffic network for spatial distribution of PM10 for traffic source; the bold black line is the location map of HCMC Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 B.Q Ho / Sustainable Environment Research xxx (2017) 1e8 surface data For FVM, time period is from January to July 2012 And the time for air pollution model TAPOM 01/07/2012 to 03/07/2012 since this is the most polluted period The calibration and validation of FVM model were conducted Meteorological parameters of temperature, wind components from FVM simulation models are calibrated and validated compared with those from observation stations in Nha Be period from 1/7/2012 to 3/7/2012 The data from the simulation results of the model were compared with actual data measured at stations with a high correlation coefficient for daily value R2 ¼ 0.693 Simulation models very good day and night temperatures in the research area 3.4 Meteorology and air pollution Result of meteorology and air quality in domain area (HCMC) is shown in Figs and The TAPOM model which is also calibrated and validated was applied to simulated air quality over HCMC The comparison between simulation and measurement at the Nha Be station shows the model simulates quite well PM10 concentrations at research area with the correlation coefficient R2 ¼ 0.72 The Nha Be station is the station where we measure the background of air quality This station has less impact from human activities Low monitoring value of the background makes higher error values Nonetheless, the correlation coefficient of 0.72 is acceptable This station is not located in the city center and should be less affected by emissions from the operation of industrial sources, transportation and residential area Then, air pollution map was established for District based on map of HCMC Because the District has a small area Meteorology and air pollution modeling cannot be done directly The result shows that almost all wards have the PM10 pollution exceeding WHO guidelines except for ward 13, 14 and 15 3.5 Mortality result With all prepared data, and based on BenMAP model theory, number of mortality is about person yrÀ1 for District for total pollution of 194,228 persons or mortality rate 0.0025% (Fig 7) Ward 10 has the highest mortality, followed by Ward and With person die every year related to PM10, District will lose 900 billion VND (45 million USD since life costs for person is million USD which is used by USEPA to estimate economic cost due to air pollution) The results of extrapolation show that the death rate related to PM10 in HCMC (population of HCMC is 7,955,000 inhabitants) is about 204 persons yrÀ1 and economic losses of 1.84 billon of USD for HCMC 3.6 Measures to reduce PM10 pollution and protect public health Together with provided decision on reducing air emission, the citizen needs to protect themselves from PM10 by using specialized face mask which can filter 80e90% of PM20 and replace the polluted Fig Wind direction on surface at a.m (upper left), 10 a.m (upper right), 12 a.m (lower left) and at 10 p.m (lower right) on 2/7/2012; the red line is the location map of HCMC Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 B.Q Ho / Sustainable Environment Research xxx (2017) 1e8 Fig PM10 concentration distribution for HCMC (mg mÀ3); the red line is the location map of HCMC Fig Mortality map for the study domain (in person); Phuong is “Ward in the map” (Phuong 13 is the ward 13 in the map) Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 B.Q Ho / Sustainable Environment Research xxx (2017) 1e8 fuel use (charcoal and wood) as well as wood-burning stove by cleaner fuel as gas or LPG The main cause of air pollution in HCMC is traffic; especially from motorcycles with more than 30% motorcycles can not meet the emission requirement Meanwhile, the fuel use has the low quality Therefore, the solutions for reducing PM10 include: (i) regulating use duration for motorcycle to reduce the number and circulation of old vehicle; (ii) providing a technical standard on gas emission for motorcycle registry; (iii) implement registration and inspection for motorcycle; (iv) improving fuel quality according to Euro standard in 2016 and Euro in 2021; (v) improving the automatic air quality monitoring system in HCMC to alert the citizen when there is high air pollution level Conclusions Emissions of PM10 for Ho Chi Minh City, Vietnam was calculated in this research Result of PM10 emissions in HCMC point out traffic is the main source of PM10 emissions and accounted for more than 83% For traffic source, the motorcycle is the main contributor and occupied about 24% of traffic emission, heavy trucks are 23%, light trucks accounted for 19% and remaining for cars and buses Simulation results PM10 dispersion in HCMC for maximum 1-h average is 250 mg mÀ3 The concentration in annual average in District is 30 mg mÀ3 District has 12/15 wards which has the air quality exceeding WHO guidelines (20 mg mÀ3), the highest annual average concentration is 48.9 mg mÀ3 in Ward and the lowest is 16.8 mg mÀ3 in Ward 13 The results from calculation shows that number of deaths related to PM10 in District is persons yrÀ1, occupied for 0.0025% in total population of 194,228 and cause economic losses of more than 45 million of USD With the results of extrapolation for HCMC, death rate related to PM10 is 204 person's yrÀ1 in total population of 7,955,000, caused economic losses of 1.836 billion of USD Acknowledgement Authors thank to Vietnam National University - Ho Chi Minh City (VNU-HCM) for providing the funding with grant number C2016_24_03 References [1] Carlos D Health imperative for urgent action on air pollution In: Integrated conference of BAQ 2014 and intergovernmental 8th regional EST Forum in Asia; 2014 Nov 19-21 Colombo, Sri Lanka [2] HEI Effects of short-term exposure to air pollution on hospital admissions of young children for acute lower respiratory infections in Ho Chi Minh City, Vietnam Boston, MA: Health Effects Institute; 2012 [3] WEF Air pollution threatens national health Davos, Switzerland: World Economic Forum; 2012 [4] Ho BQ, Clappier A, Francois G Air pollution forecast for Ho Chi Minh City, Vietnam in 2015 and 2020 Air Qual Atmos Health 2011;4:145e58 [5] HEPA Report 2006 air quality in Ho Chi Minh City Ho Chi Minh city, Vietnam: Ho Chi Minh Environmental Protection Agency; 2006 [6] HEPA Report 2010 air quality in Ho Chi Minh City Ho Chi Minh city, Vietnam: Ho Chi Minh Environmental Protection Agency; 2010 [7] Ho BQ Optimal methodology to generate road traffic emissions for air quality modeling: application to Ho Chi Minh City [Ph.D Dissertation] Lausanne (Switzerland): Federal Institute of Technology; 2010 [8] Belalcazar LC, Fuhrer O, Ho MD, Zarate E, Clappier A Estimation of road traffic emission factors from a long term tracer study Atmos Environ 2011; 2009(43):5830e7 [9] Zarate E, Belalcazar LC, Clappier A, Manzi V, Van den Bergh H Air quality modelling over Bogota, Colombia: combined techniques to estimate and evaluate emission inventories Atmos Environ 2007;41:6302e18 [10] EMEP/EEA The EMEP/EEA air pollutant emission inventory guidebook Copenhagen Denmark: European Environment Agency; 2009 Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research (2017), http://dx.doi.org/10.1016/j.serj.2017.01.001 ... is the location map of HCMC Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research... the location map of HCMC Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on human health, Sustainable Environment Research... person); Phuong is “Ward in the map” (Phuong 13 is the ward 13 in the map) Please cite this article in press as: Ho BQ, Modeling PM10 in Ho Chi Minh City, Vietnam and evaluation of its impacts on