Modeling of the Dispersion of PM10 and Proposing Measures for Reducing PM10 Pollution Levels: the Ca

Global Perspectives on Geography (GPG) Volume 3, 2015 www.as‐se.org/gpg doi: 10.14355/gpg.2015.03.001

Modeling of the Dispersion of PM10 and Proposing Measures for Reducing PM10 Pollution Levels: the Case of Thu Duc, Vietnam Ho Quoc Bang Institue of Environment and Natural Resources / Vietnam National University in Ho Chi Minh.

Address: 142 To Hien Thanh Street, District 10, Ho Chi Minh City, Viet Nam. bangquoc@yahoo.com

Abstract Thu Duc district is located on the east ‐ north of Ho Chi Minh City (HCMC). Currently, Thu Duc District doesn’t have statistical data about air pollution therefore; overview of air pollution status can’t be assessed as well as no measures to reduce the increasing of air pollution in the District. Therefore, the objectives of this research are to conduct emission inventories of Particle Matter PM10, then many models such as FVM and TAPOM are used to simulated the dispersion of PM10 in the area. The main sources of PM10 emission are from road transport, industry and households. The emission inventories results show that emissions of industrial sources contribute the largest PM10 particulate pollution followed by traffic source and the household source is negligible compared to the two sources above. For traffic source, studies have calculated emission of PM10 generated by each type of vehicles. Among that, motorcycles are the main sources of PM10. PM10 emission from Industrial source, transport and households respectively: 11 985 tons / year, 7,579 tons / year, 188 tons / year. Simulated results of meteorological paterns and airpollution for pollutants PM10 during the study period of July 2012, the simulated results are very similar to the monitored results.

The research also identified number of solutions to reduce PM10 level for Thu Duc District. The results obtained from the subject certainly have great significance in environmental protection and management of environmentally sustainable atmosphere in Thu Duc District.

Keywords Fine Particle Matter of PM10; Air Pollution; EMISENS Model; FVM Model; TAPOM Model; Vietnam

Introduction Thu Duc District is located in Eastern ‐ the North and the gateway to the east of Ho Chi Minh City. Thu Duc District has an area of 47.76 km2 and the population of 500 850 people with the population density of 10 487 persons/km2 [1].

The District has approximately 150 full‐scale plants producing large (mainly concentrated in industrial parks, export processing zones) and thousands of small factories, industrial parks and export processing zones in the District (Dist.) include: Binh Chieu Industrial Zone, Export and Import Zone (EPZ) of Linh Trung I, Linh Trung II EPZ. The District has three major road that runs through all of the national highway: Hanoi Highway, Highway 13 and Highway outer ring with a sizable amount of vehicle traffic. It is what has made the District's air quality more seriously polluted.

According to the monitoring and reporting of environmental quality monitoring annual Environmental Protection Dist. HCM recent years the average concentration of dust in the air exceeds a high standard to allow existing 2‐7 times over the years in the area of Thu Duc District, along the Hanoi Highway. Given the population growth, industrial development and transportation in Thu Duc District today, the dust concentration will continue to rise.

Therefore, this research conducted calculate dust emissions from industrial sources, transportation and activities and use simulation models and meteorological FVM simulation models for air quality mapping TAPOM PM0 spread of dust in Thu Duc district. The study also proposes a number of measures to control and reduce pollution of PM10 dust in Thu Duc District.

Method and Data Method Air quality models are mathematical tools described transport processes, diffusion and transfer of the chemical reactions of pollutants in the air. The air quality model calculations based on the input data set includes: emission data, meteorological data, topographic data and produce results concentrations of air pollutants to describe air

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quality and shape distribution maps of pollutants for the study area.

FIG.1 THE STEPS AND PERFORM CONTENT

Thu Duc area with a maximum length of 12 km and a maximum width of 10 km, but in the research, the authors have made to the region spanning the inner districts of the city. Ho Chi Minh City including Thu Duc district with grid size 34 km x 30 km, each cell has an area of 1 km2 grid then extract results in Thu Duc District for the following reasons: 

If you own simulation Thu Duc District, there is no monitoring data automatically and continuously fine dust in the wind PM10 to calibrate and test the model results.



Thu Duc district size too small 12 km x 10 km, not suitable for urban simulation modeling and TAPOM FVM.

Emission Inventory This study calculates PM10 dust emissions from the following sources: traffic, industrial and domestic. Statistics emissions from industrial sources author legacy data sources emission of waste gases emissions source statistics program of the Department of Natural Resources and Environment Ho Chi Minh City in 2013 conducted emissions from domestic sources, the authors calculate emissions based on population density and the coefficient of PM10 dust emissions per capita. For the transportation of waste sources, the author inherited the investigation results, survey data input topics ministerial level "Research methodology perfected emissions from road transport operations: Apply rated emission rates for the city by Dr. Ho Quoc doing all responsibility for database input for EMISENS model.

EMISENS model [3] is a model used to calculate the emission load due to traffic operations. EMISENS model is a new method to calculate traffic emissions using the combined approach, "Top‐down" and "bottom‐up".

Simulation Models Models FVM (Finite Volume Model), was built by LPAS ‐ EPFL, the Eulerian model 3D space, using the terrain under the grid resolution volume limit. FVM is closed turbulence model, the equations of this model include momentum equation, continuity equation, the equation preserves moisture and heat equations and diffusion kinetic energy tangled mess. Model simulation results FVM meteorological input to the simulation model TAPOM air quality.

Air quality model used for this study is TAPOM (Transport and Photochemistry Mesoscale Model). TAPOM built by PAS ‐ EPFL ‐ metabolism simulation of air pollutants in the atmosphere. This is a model of chemical transport and optical three‐dimensional Euler modeled. Air quality models are mathematical tools described transport processes, diffusion and transfer of the chemical reactions of pollutants in the air. This model includes many modules to

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simulate the metabolic processes of atmospheric pollutants such as chemical reactions, transport processes, process emissions, and sedimentation process contaminants. The chemical changes were simulated using parameters mechanism (RACM ‐ Regional Atmospheric Chemistry Mechanism) and ISORROPIA modules [2], [4]. In the model TAPOM each volume includes 6 sides and angles based on 8 points. These points can be selected by the user from which to create any public grid.

Input Emissions of PM10 in Thu Duc Industrial Source: Study collected 282 exhaust gas emission sources throughout the HCMC including 37 exhaust emission sources such as boilers, generators, furnace, ... the distribution of plants in and outside industrial parks, export processing zones of Thu Duc District.

Air emissions generated from industrial sources is calculated based on the following formula: Gi = Σ Kj x Nj Where: Gi is estimated amount of pollutant i (kg/day), Kj: The emission factor of the fuel kg/kg or kg/m 3 in Table 1, Nj: Amount of fuel j kg /d or m3/day TABLE 1. PM10 EMISSION FACTOR OF FUEL

Fuel PM10 emission factor

DO g/kg 0,00063

FO g/kg 0,00075

COAL g/kg 0,00693

Firewood g/kg 0,0036 (WHO, EMEP/EEA, 2009)

Note: Specific weight is 0.87 kg DO/l; Density of fuel oil was 0.96 kg/l Based on the amount of fuel used, traffic, emissions from boilers, generators, ... and the emission factor in Table 1 we calculate the emission load for the industry.

Source activities: population density in Thu Duc district is 500,850; Emission factor 0.013 kg PM10/person/year for using as fuel gas and 2,433 kg PM10/person/year for using as coal.

Traffic sources: inheritance and survey of more than 400 heavy trucks consultation, 900 cars, 550 buses, 1400 motorcycles and 600 light trucks. The research organized survey traffic congestion in 52 routes which is divided into 5 road categories in HCMC for both weekdays and weekends.

For calculating the PM10 emission from traffic sources, this research used the EMISENS model for generating EI. The main specifications of EMISENS are: (i) the model is able to compute a total amount of emissions and distribute it in time and space using a methodology fully compatible at the same time with a top‐down and a bottom up approach. (ii) The model is able to compute the emissions and to compute the uncertainties due to input parameters in using Monte‐ Carlo method (MC). (iii) The model formulation is based on a well known and well‐referenced methodology (Copert IV) [5].

To select normal phase simulation takes into account two main principles are: (i) Phase simulation to represent a period of pollution. (ii) This is one of the worst cases of pollution in Ho Chi Minh City. Generally, the period of time for this simulation lasts about 3‐4 days and during this period we have as many measuring data quality monitoring of air pollution and meteorological better [5]. However, by monitoring data and meteorological data on dust pollution at monitoring stations should be selected incomplete simulation time meteorological and air quality is 3 to 03 days from 01/07/2012 to 03/07/2012. This time period is full of meteorological parameters as well as data on PM10 dust concentrations at monitoring stations.

To conduct meteorological FVM simulation, the authors collected the boundary conditions and initial conditions for this model are the analysis of data from global weather patterns of the NCEP (National Centers for Environmemtal Prediction). This data has a resolution of 2.5 x 2.5 degrees horizontal theodolite with 17 pressure levels, at the moment 0Z, 6Z, 12Z and 18Z. This data is updated continuously from 01.01.1948 to date. Meteorological data (Meteo) [7]. Input data for FVM model includes terrain elevation, the form of surface coatings, surface and ground water, soils, vegetation and percentage of soil temperature annual average. These data were taken at a resolution of 1km from the USGS (US Geological Survey ‐ Agency of the United States Geological Survey) [8]. Private terrain data with the data resolution is 1 kilometer [6].

The meteorological data as input in the model is used TAPOM result of FVM model, in which the boundary conditions are controlled by the wind and temperature from the results of large‐scale models. With both climate models and air quality, we can use the domain 34 km x 30 km , with each grid cell has an area of 1 km2 and covers the entire central area of Ho Chi Minh City.

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Result and Dicussions Results of PM10 Emission Inventories TABLE 2 TOTAL EMISSIONS DUST PM10 BY SOURCE IN THU DUC DISTRICT

STT 1 2 3

Source generated Industry Conditions of life Traffic

Dust tonnage PM10 (tonne/year) 11,985 188 7,579

Result calculates waste transmitting from pollution sources show traffic industrial and operational action is dust PM10 contributing source chiefly. Conditions of life action contributive that PM10 dust be is negligible in Township's general dust pollution tonnage PM10 sum Thu Duc. Spatial Distribution of PM10 Statistics and distribution of air pollution load from sources of pollution in HCMC is spatially implemented by version 11 software Mapinfo Using computational domain size is 1 km2 grid (1 km x 1 km) and the 34 x 30 points respectively in each direction x and y. Results distribution of air pollution load generated by each source according 1km2 grid cell size is one of the first to run TAPOM model..

FIG.2 DISTRIBUTION MAP FOR INDUSTRIAL PM10 EMISSIONS (UNIT G/H.KM2); THE BLUE COLOR IS THE INDUSTRIAL EMISSION SOURCES, RED CELLS ARE EMISSION LEVELS IN THE GRID.

Distribution of air pollution emissions spatially is dependent on sources of pollution. For industrial sources, emissions‐based distribution location coordinates distribution of plants in areas of the research area (the exact location of factories). For household sources, emission distributions are based on population density. For traffic sources, emission distribution is calculated based on the length of each grid cell (mean area with high traffic, the network will have high emissions). PM10 emissions from industrial sources are distributed on each grid, as shown in the FIG.2 below:

FIG.3 DISTRIBUTION MAP FOR LIVING PM10 EMISSIONS (UNIT G/H.KM2); DFFERENT COLORS REPRESENT EMISSIONS IN THE GRID

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Figure 2 shows the emission load from industrial discharges in each grid cell every hour (unit g / h.km2) in space. The results show that load PM10 dust emissions in the range of 0 ÷ 1.27 tons / h mainly concentrated in the wards as Linh Trung Truong Tho. Fine dust arising PM10 concentration in plants such as thermal power, steel, food, textile, etc.

Figure 3 shows emission load of domestic waste resources on each grid cell (unit g / h.o grid) in space. The results show that load PM10 dust emissions in the range of 0 ÷ 2,020 g / h mainly concentrated in the wards densely populated as the Linh Chiểu ward, Linh Tây ward, Bình Thọ ward, Linh Xuân ward…

FIG. 4 DISTRIBUTION MAPS FOR TRAFFIC PM10 EMISSIONS (UNIT G/H.KM2); THE BLUE LINE IS ROAD NETWORK; RED CELLS ARE EMISSION LEVELS IN THE GRID.

Figure 4 depicts the average load of PM10 emissions from transportation sources (in g / h.o grid) in space. The results showed that the average load of PM10 emissions in days ranged from 0 ÷ 1.84 tons / h. Download the most emissions are concentrated in the streets with more traffic as Highway 13, Highway Ha Noi,... load PM10 from traffic mainly concentrated in the wards as: Linh Xuan, Linh Trung Truong Tho, Binh Tho. The reason is that with the central district major roads passing through the flow of vehicles through the high street are mostly heavy trucks and intersections often occurring traffic jams.

Result of Meteoric Simulation Model FVM

FIG. 5 COMPARE OBSERVATION AND WIND VELOCITY ONOMATOPOEIA PRACTICALLY IN DAYS FROM 1/ 7/ 2012 TO 3/ 7/ 2012 AT NHA BE (DOTTED LINE IS MONITORING, SOLID LINE IS SIMULATION)

Results from simulation model of FVM wind velocity from day 3/7/2012 to day 1/7/2012 similarities with actual measurement results in Nha monitoring stations (Figure 5). Maximum wind speed in the period from 12 am to 4 pm, which means the maximum wind velocity corresponding to the ground the moment the most heated make atmospheric disturbance (unstable) most.

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FIG. 6 WIND FIELD AT GROUND LEVEL AT 4:00, 10:00, 12:00, 22:00 ON 7TH JULY 2012

Temperature results from FVM simulation models and results in temperature measurement observation stations in Nha Be period from 1/7/2012 to 3/7/2012 similar each day (Figure 6). The data from the simulation results of the model were compared with actual data measured at stations on the day Nha Be simulation with a high correlation coefficient R2= 0.693. Simulation models very good day and night temperatures in the research area. Simulation results warmest in the period from 12 am to 2 pm, the temperature fluctuated between 310C ÷ 32,50C, this is also the period with the highest temperature in Nha Be observation stations. However simulate nighttime temperatures lower than this measured temperature can be explained as a result of the NCEP global model (which students use to run Nesting boundary conditionin one way as a condition of margin) was also lower than the actual night

FIG. 7 COMPARISON (LEFT PIX) AND OBSERVATION AND TEMPERATURE ONOMATOPOEIA AUTOCORRELATION (PIX RIGHT) IS ACTUAL IN DAYS FROM 1/ 7/ 2012 TO 3/ 7/ 2012 AT NHA BE. DOTTED BLACK LINE IS MONITORING, SOLID BROWN LINE IS SIMULATION

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Model Simulation Results TAPOM

10h

12h

FIG.8 MAPS OF THE CONCENTRATION PM10 AT THU DUC DISTRICT AT 10H, 12H; 2/7/2012

16h

22h

FIG.9 MAPS OF THE CONCENTRATION PM10 AT THU DUC DISTRICT AT 16H, 22H; 2/7/2012 TABLE 3: PM10 CONCENTRATION IS MERIDIAN IN THU DUC DISTRICT ON 2, JULY, 2012 (TB: AVERAGE)

Simulation time Concentration PM10 (µg/m3 ) Simulation time Concentration PM10

1 282 15 9

2 286 16 38

3 280 17 3

4 285 18 115

5 292 19 142

6 382 20 124

7 414 21 96

8 589 22 90

9 613 23 95

10 457 24 156

11 411 TB 24h 230

12 13 272 8 QCVN 05: 2013 150

14 82 WHO 25

According to the simulation results from the model TAPOM on PM10, PM10 pollution in areas hardest in District 24‐ hour average concentrations exceeding 1:53 times the QCVN 05: 2013 / BTNMT(National Standards for air quality around) and exceeded 9.2 times the WHO criteria (2005). Period of time from 7 am to 12 pm is time of the highest concentrations of PM10, as red boilers, running ... This is also the peak period so the amount of traffic vehicles involved very crowded, especially around 6am to 9am time locality District regular traffic jams occur.

Compare the Correlation between the Results of Model and the Monitored Results The comparison between simulation and measurement at Nha Be station shows the model simulations quite well PM10 concentrations at research area with the correlation coefficient hourly is R2 = 0,534. Nha Be Station as the station platform can be little impact from human activities; less the value of the background makes the error values are usually higher. So the correlation coefficient for hourly is 0.534 and acceptable. This station is not located in the city center should be less affected by emissions from the operation of industrial sources, transportation and living.

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Furthermore wind direction is east ‐ south to beam contamination away from Nha Be station so PM10 concentrations at this point Nha Be very low concentrations fluctuate between 0 ÷ 10 g/m3.

FIG. 10 COMPARISON (LEFT PANEL) AND CORRELATION (RIGHT) PM10 CONCENTRATIONS SIMULATED AND AT MONITORING STATIONS NHA BE. RED (SQUARE) LINE IS THE RESULTS OF MONITORING; BLUE (RHOMBUS) LINE IS THE RESULTS OF SIMULATION

Conclusions and Recommendations Urbanisation has led to environmental pollution worsened. According to the latest announcement in October 2013 of the WHO and the US ‐ EPA, the fine dust PM10 and ozone are two typical air pollution and considering as pollution indicator for urban areas. Thu Duc is a district which is located in the top of particulate pollution areas of Ho Chi Minh City. Statistics and Research has calculated PM10 emissions and simulated dispersion ‐ distribution of PM10 pollution levels in the area of Thu Duc District. The first result shows the current status and the impact of industrial activities, transport and activities to the air quality through the indicators of PM10. The calculation results show that emissions of industrial sources contribute the largest PM10 particulate pollution followed by traffic source. The household source emission is negligible compared to the two sources above. The traffic source accounted for more than 38% of total PM10 emissions in Thu Duc. For traffic source, the motorcycle is the most emissions and occupied about 24% of traffic emission, 23% of heavy trucks, light trucks accounted for 19% and remaining for cars and buses.

Simulation results meteorological conditions and air quality for pollutants PM10 during the study period are similar to monitored results. From the research results, numbers of solutions are susgested to reduce PM10 pollution in Thu Duc District. The results of the distributed emissions of pollutants PM10 in Thu Duc District is a reliable basis for the formulation, strategic planning and air pollution mitigation, contributing to pollution reduction for the whole city of Ho Chi Minh.

It is urgent need to promulgate regulations emission quota of air pollution, including dust emissions for industrial sources. Displaced plants much dust as mechanical, thermal, concrete, ..away from populated areas. Rapid measures to reduce dust pollution in the Linh Xuan Ward, Linh Trung Truong Tho ... Requires installation of air pollution control system in ensuring sources of Vietnam to set standards for emissions before escaping into the environment.

The number of vehicles increased traffic increasing in the area led to traffic jams occur frequently, including motorcycles and heavy trucks are two means of PM10 dust arising. So the city needs to develop and finish systems of public transport as schedule, to be able to replace the motorcycle. Continue to inventory emissions for all pollutants CO, NOx, SO2, etc. thereby establishing development plans for clean air HCMC. Directions for further research should be conducted studies evaluating the effects of PM10 dust impact on the health of residents in the District. At the same time researchers calculated for pollutants in areas throughout the city and district of Ho Chi Minh detail.

ACKNOWLEDGMENT

This research is funded by Vietnam National University HoChiMinh City (VNU‐HCM) under grant number C2014‐24‐ 03. The authors thank Vietnam National University in Ho Chi Minh for providing the fund. A special thank is also addressed to The Institute for Environment and Resources for for their precious collaboration in this work and

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facilities supports.

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Ho Chi Minh City Department of Statistics (2013), "Statistical Yearbook (2012)". Tp. Ho Chi Minh City

[2] Gong W, Cho H (1993). “A numerical scheme for the integration of the gas phase Chemical rate equations in threedimensional atmospheric models”. Atmospheric Environment, 27A, 2147–2160.

[3] Q.Bang. HO (2012). “Research improvement methodology emissions from road transport activities: Applying emissions assessment for HCM”. Technical report for VNU‐HCM project level.

[4] Q.Bang. HO., Clappier, A. and Blond, N. (2014), Fast and Optimized Methodology to Generate Road Traffic Emission Inventories and Their Uncertainties. Clean Soil Air Water, 42 (10) : 1344–1350. doi: 10.1002/clen.201300261 (IF: 2.046).

[5] Q.Bang, HO, Clappier, A., 2011. Road traffic emission inventory for air quality modelling and to evaluate the abatement strategies: a case of Ho Chi Minh City, Vietnam. Atmospheric Environment Journal. Vol 45, Issue 21 (2011) pp. 3584‐3593.

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[6] Q.Bang, HO., Clappier, A., Golay F., 2011. Air pollution forecast for Ho Chi Minh City, Vietnam in 2015 and 2020. Air Quality, Atmosphere & Health, Volume 4, Number 2, p.145‐158 (IF: 1.979).

[7] Stockwell WR, Kirchner F, Kuhn M, Seefeld S (1997). “A new mechanism for regional atmosphere rich chemistry modeling”.

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[8] Zarate, E., (2007). Understanding the Origins and Fate of Air Pollution in Bogota, Colombia. Doctoral thesis, N° 3768, EPFL. [9] http://edc.usgs.gov. (Referenced there‐in December 2013) [10] http://www.esrl.noaa.gov/psd/data/reanalysis/reanalysis.shtml. (Referenced there‐in December 2013) [11] http://www‐tem.jrc.it. (Referenced there‐in December 2013)

Bang Q. Ho was born in Vietnam, on 17/12/1979. He got Docteur ès Sciences (Ph.D.) degree on Environmental Science (Emission inventories and air quality modelling) at the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland in 2010. He is doing research on Climate Change, Energy and Air quality fields.

He got Master degree on Environmental Science at the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland in 2005. From 1997 to 2001: he did Bachelor of Analytical Chemistry at the University Sciences Natural / Vietnam National University in Ho Chi Minh City. From 2001 to 2011 he has worked for several Labs in IER (System laboratories lab, Air quality lab), EPFL (LPAS, LASIG) and also in French National Center for Scientific Research ‐ France on Emission inventory, Modelling of Meteorology and Air pollution, monitoring of air quality and water quality, Climate change. In 2011 he worked at Duke University, USA as visiting scholars on Energy and Environment. He is now working as a Consultant on Air quality expert for German Technical Cooperation (GIZ) under two projects “Clean Air For Smaller Cities In ASEAN Region” and “Sustainable for Port Development in ASEAN Region” Dr. Ho is also currently Director of Air Pollution and Climate Change Department/Institute of Environment & Resources (IER)/Vietnam National University, HoChiMinh City (VNU/HCM). He teaches many courses on “Sustainable Energy Use”, “Climate Change”, “Control of air pollution and noise” and “environmental modelling” for master and engineer levels.

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