diurnal variation of tropospheric ozone (o3 ... · bureau of statistics of padang city (2015) noted...

VOL. 12, NO. 24, DECEMBER 2017 ISSN 1819-6608

ARPN Journal of Engineering and Applied Sciences ©2006-2017 Asian Research Publishing Network (ARPN). All rights reserved.

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7012

DIURNAL VARIATION OF TROPOSPHERIC OZONE (O3)ANDITSPRECURSORS (CO AND NO2) DUE

TO TRANSPORTATIONACTIVITY IN THE ROADSIDE AREAS IN PADANG

CITY, INDONESIA

Vera Surtia Bachtiar1, Purnawan

2 and Muhammad Ammar

1

1Environmental Engineering, Andalas University, Padang, Indonesia 2Civil Engineering, Andalas University, Padang, Kampus Limau Manis, Universitas Andalas Padang, Indonesia

E-Mail: [email protected]

ABSTRACT

The study aims to analyze the diurnal variation of the concentration of ozone (O3) and its precursors, carbon

monoxide (CO) and nitrogen dioxide (NO2) in ambient air, as well as its relationship with the temperature, solar radiation

and traffic characteristics on the roadside area in Padang city. The sampling of O3 and its precursorswere carried out on

three locations on roadside areas, which is classified according to its function, Ganting Road representing local roads,

Bagindo Aziz Chan Road representing collector roads and Khatib Sulaiman Road representing arterial roads. The result

showed the highest concentrations measured on the Khatib Sulaiman Road with the highest O3 concentrations occurred at

13:00 to 14:00, while the highest concentration of CO and NO2 occurred at 17:00 to 18:00. The increase of solar radiation

and the surface temperature is directly proportional to increasing concentrations of O3 and inversely proportional to the

concentration of CO and NO2. The increase of volume and traffic density is directly proportional to increasing

concentrations of O3, CO and NO2, while traffic speed is inversely proportional to the concentration of O3, CO and NO2.

However, the relationship between the traffic speed and NO2 concentrations tends to be weak and insignificant.

Keywords: roadside, diurnal variation, ozone, carbon monoxide, nitrogen dioxide.

INTRODUCTION

Transportation is very valuable and necessary to

support the progress of the major cities in the world, on

the other hand the increasing growth rate of transportation

will make negative effects such as increased air pollution

(Wang et al., 2017). The contribution of motor vehicle

exhausting emissions as a source of air pollution is very

significant (Yang et al., 2011; Cui et al., 2015). The

growth rate of motor vehicles in Indonesia has reached

more than 10% per year, this condition is followed by the

growth rate of the street which is not comparable, only 2%

per year. It is the dominant factor that caused the increase

of air pollution by motor vehicle, thus further aggravate

the condition of the air in various cities in Indonesia.

The amount of air pollution contributed from

transportation will also disrupt the gas composition

balance in the atmosphere, especially the increase in the

concentration of ozone in the troposphere. This is caused

by the motor vehicles that emit gases such as nitrogen

oxides (NOx) and carbon monoxide (CO), which acts as a

gas-forming ozone (ozone precursors) on the surface

(Tiwary et al., 2015).

Ozone is a triatomic molecule composed of three

oxygen molecules and are more unstable when compared

with oxygen. Ozone in the Earth's atmosphere is spread in

two layers, stratosphere and troposphere. Ozone in the

stratosphere has a role to restrain ultraviolet (UV)

radiation. While ozone in the troposphere (surface ozone)

is a secondary pollutant formed by the photochemical

reaction of its precursors with the help of sunlight. Surface

ozone is a primary pollutant in smog (smoke and fog) and

a strong photochemical oxidant which cause various health

problems to humans and plants. Surface ozone is also

associated with the climate change or global warming, that

is because surface ozone is included in the category of

greenhouse gases (Mbuyi, 2001).

One of the ozone precursor is nitrogen oxides

(NOx). NOx is a group of gas contained in the atmosphere

that consists of nitrogen monoxide (NO) and nitrogen

dioxide (NO2). In ambient air, NO can be oxidized (NO2)

which are toxic. Research shows that NO2 gases are four

times more toxic than NO. NO2 can irritate the nose and

throat, especially the people with asthma and increase

susceptibility to respiratory infections (Weichenthalet al.,

2015).

Besides NO2, carbon monoxide (CO) is also an

ozone precursor in the surface (He et al., 2017). Central

Bureau of Statistics of Padang City (2015) noted the

number of vehicles in Padang city amounted to 427,235

units in 2014. The large number of these vehicles will

affect the increasing the number of pollutants, especially

CO (Bachtiar et al., 2016a) and NO2 (Bachtiar et al., 2017)

which emitted into the air from vehicle exhaust, it is also

characterized by rising concentrations of ozone (O3).

Based on the influence and impact and also the increasing

the amount of pollutants in the air due to transportation

activities, especially in the roadside area, then the

measurement of O3, CO and NO2 concentrations in

ambient air becomes very important.

Research on determining the concentration of O3

in Padang City has been done by Bachtiar et al. (2015) but

in the research O3 concentration monitoring was only

mailto:[email protected]




7013

performed for an hour at each sampling point locations

and not concentrated on the roadside area. Based on this

research, further studies are needed to determine the

concentration of O3 in the roadside area.In this study,

besides monitoring O3, monitoring of ozone precursors is

also performed. However, in this study ozone precursors

which only monitored CO and NO2, because the source of

the gas ozone precursors produced is due to the activity

motor vehicles were only CO and NO2. In addition, at the

roadside area the source of other pollutants which can emit

gases ozone precursors such as CH4 and VOCs could not

be found.

MATERIAL AND METHODS

Sampling locations were set at the three-point

which differentiated by the classification of roads

according to its function, namely local road, collector road

and arterial road. Based on its condition, the road that can

be used as the location of sampling is Ganting Road

representing local road, Bagindo Aziz Chan Road

representing collector road and Khatib Sulaiman Road

representing arterial road. Monitoring was conducted

every hour for 24 hours in order to get the diurnal

variation of O3 concentrations and gas precursors.

Meteorological measurements performed every15

minutes during the sampling. Meteorological conditions

measured at each sampling is temperature (oC), air

pressure (mmHg) and relative humidity (RH) were

measured using digital pocket weatherman, solar radiation

is measured using a lux meter, wind direction indicated

using a compass and wind speed is measured using

anemometer. Gas sampling O3, CO and NO2 in ambient air

sampling conducted by the active method using a gas

sampler ambient (impinger).Traffic characteristics

measured were the number of vehicles, traffic volume, and

traffic speed and traffic density. The traffic speeds is

measured using radar speed gun meter.

Statistical analysis was conducted to determine

the relationship between O3 and its percursors, such as

regression analysis, coefficientof correlation, coefficient of

determination and analysis varians (anova).

RESULTS AND DISCUSSIONS

Comparison of the number of vehicles in each

research location can be seen in Figure-1.

Figure-1. Comparison of number vehicles on research location.

The measurement results show that the highest

number of vehicles on the Khatib Sulaiman Road, then on

Bagindo Aziz Chan Road and the lowest on Ganting Road.

The high number of vehicles on the Khatib Sulaiman Road

and Bagindo Aziz Chan Road caused by the number of

activities, such as offices, shopping centre and educations

around the road. MeanwhileGanting Road is just a

residential area.

There are three main variables needed to explain

the characteristics of traffic. It is traffic volume, traffic

speed and traffic density.Traffic volumes in the three

research location in the daytime was higher than in the

evening, with the pattern of traffic volume fluctuation tends

to similar. The pattern of fluctuations in the volume of

traffic generally increases to twice the volume; it can be

seen in Figure-2.

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Chan Road

Khatib Sulaiman

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Figure-2. Comparison of traffic volume on research location.

On the morning there was an increase in traffic

volume from 04.00 until 08.00. The peak hours on the

morning occurred at 07.00-08:00. The increased volume of

traffic re-occurred around 12:00 until 18:00, with the peak

hours occurred at 16.00-18.00.The measurement results

showed that Khatib Sulaiman Road has the highest traffic

speeds average compared to the other two locations. This is

due to the street is wider and the side friction is low, so that

the vehicle passing this street have more space than

Bagindo Aziz Chan Road which have high side friction and

Ganting Road which has smaller width and the many

settlements which causes the driver tends to reduce the

speed of their vehicle. The comparison of the speed of

traffic on the three research locations can be seen in Figure

3.The pattern of traffic density fluctuations at three

research locations can be seen in Figure-4.

Comparison of diurnal variation of the

concentration of O3, CO and NO2 in each research location

can be seen in Figure-5. Based on Figure-5, O3, CO and

NO2 concentration measurement results in the three

research location are still below the quality standard,

According to the Indonesian Government Regulation No.

41 of 1999, on Air Pollution Control, the ambient air

quality standard for an hour measurements for CO gas is

30,000 g / m3, NO2 of 400 g / m

3 and O3 is 235 g / m

3.

Figure-3. Comparison of traffic speed on research location.

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Figure-4. Comparison of traffic density on research location.

Based on Figure-5, the pattern of diurnal variation

of CO and NO2 tend to be higher in the morning and

evening, this is due to the high activity of the use of

vehicles in these hours. While diurnal variation of O3

surface tends to be higher in the daytime than in the

evening, because in the daytime the process formation of

O3 involves ozone precursor, it is also resulting in lower

concentrations of CO and NO2 in the daytime. However,

O3 concentrations can still be measured despite of the

absence of solar radiation in the evening. According to

Xiao et al. (2017) the decrease in surface temperature

causes the density of the air at the surface is greater than

the air above the surface, it then causes the air drops which

followed the transport of ozone from the upper layer to the

surface.

The relations between O3, CO and NO2

concentrations with solar radiation in the three research

locations can be seen in Figure-6, Figure-7 and Figure-8.

Based on these figures, in the morning until noon,

photochemical production will increase along with the

increase of solar radiation, which causes an increase of O3

concentrations and decreased concentrations of ozone

precursors. While on the afternoon, photochemical

production process decreases followed by solar radiation,

which causes a decrease in the concentrations of

O3.According to Han et al. (2011), diurnal variation

patterns of O3 tend to be similar to the pattern of the solar

radiation, where the concentration of O3 will reach a

maximum point during 1-2 hours after the solar radiation

reaches its maximum point.The statistical test relationship

of O3, CO and NO2 concentration with the solar radiation

can be seen in Table-1.

Based on statistical test the relationship between

O3 concentration and the solar radiation in three research

locations has correlation values (r) which is positive, with

interpretation of relations is from strong to very strong

(Pudasainee et al., 2006; Tu et al., 2007; Kumar et al.,

2010, Tong et al., 2016). The positive correlation value

between the intensity the solar radiation and surface ozone

concentration means the increase in the intensity the solar

radiation also results in increased surface ozone. The

relationship between the concentration of CO and NO2 with

the solar radiation in three research locations show that the

correlation values (r) is negative, with the interpretation of

relations is strong enough to strong.

The solar radiation is more intense in the daytime

make the surface temperatures warmer (Bachtiar et al,

2014). During the day the surface ozone concentration is

very high due to higher surface temperatures. This

indicates that the air temperature cused by solar radiation

tends to create high ozone concentrations. It is also

resulting in the decrease in the concentration of ozone

precursors (Wang et al., 2017).

Statistical test relations of O3, CO and NO2

concentrations with temperature is shown in Table-2. The

relationship between the O3 concentration and the

temperature in three locations show that correlation values

(r) is positive, with the interpretation of relations is very

strong, while the relationship between the concentration of

CO and NO2 with the temperature in three locations show

that correlation values (r) is negative, the interpretation of

relations is strong.

Based on Sayegh et al. (2016) temperature is

inversely proportional to the concentration of pollutants

(CO and NO2), which means that the higher temperature,

the concentration of pollutants (CO and NO2) are getting

low. The decrease in the concentration due to the high air

temperature, air density at the surface will be lower than

above the surface. It causes convection flow occurs

upwards which brought the pollutants causing the

concentration of pollutants in the surface to be reduced.

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Figure-5.Diurnal variations of O3, CO dan NO2 concentrations on research location.




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Figure-6. Relations of O3, NO2, and CO concentrations with solar radiation on ganting road.

Figure-7. Relations of O3, NO2, and CO concentrations with solar radiation on Khatib Sulaiman road.

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Figure-8. Relations of O3, NO2, and CO concentrations with solar radiation on Bagindo Aziz Chan road.

Polutant concentrations is also influenced by

temperature (Bachtiar et al., 2016b) . Relations of O3, CO

and NO2 concentrations with temperature similar to the

solar radiation, there is a very strong relationship between

temperature and surface ozone concentrations, it can be

seen in Figure-9 to Figure-11.

Table-1. Statistical test relations of O3, CO and NO2 concentrations with solar radiation.

Correlations Regression Anova

r R2 Type Regression Formula Fvalue Fcritical value

Ganting Road (Local Road)

O3 0.874 0.764 Exponential y = 39.978e0.001x

16.430 4.844

CO -0.595 0.354 Polynomial y = -0.0001x2 + 0.0791x + 389.009 5.745 3.467

NO2 -0.630 0.397 Logarithmic y = -2.524 ln(x) + 50.211 7.245 4.844

Bagindo Aziz Chan Road (Collector Road)

O3 0.924 0.854 Linear y = 0.071x + 58.870 64.280 4.844


NO2 -0.562 0.315 Exponential y = 65.189e-0.00001x

5.068 4.844

Khatib Sulaiman Road (Arterial Road)

O3 0.952 0.907 Logarithmic y = 17.838 ln(x) + 10.054 107.511 4.844


NO2 -0.713 0.508 Exponential y = 82.473e-0.00001x

11.360 4.844

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Figure-9. Relations of O3, NO2, and CO concentrations with temperature on ganting road.

Figure-10. Relations of O3, NO2, and CO concentrations with temperature on Khatib Sulaiman road.

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Figure-11. Relations of O3, NO2, and CO concentrations with temperature on Bagindo Aziz Chan road.

Table-2. Statistical test relations of O3, CO dan NO2 concentrations with temperature.

Correlation Regression Anova



O3 0.957 0.916 Polynomial Y = 0.547x2 – 30.107x + 450.753 114.967 3.467

CO -0.724 0.524 Polynomial Y = -5.937x2 + 385.44x – 5899.493 11.561 3.467

NO2 -0.716 0.513 Polynomial Y = -0.604x2 + 36.875x -521.507 11.055 3.467


O3 0.977 0.955 Polynomial Y = 0.714x2 – 36.642x + 513.451 223.803 3.467

CO -0.877 0.769 Polynomial Y = -6.638x2 + 432.369x – 6449.860 34.982 3.467

NO2 -0.659 0.434 Polynomial Y = -0.988x2 + 59.209x – 817.672 8.066 3.467


O3 0.939 0.881 Linear Y = 9.283x – 199.231 163.224 4.301

CO -0.736 0.541 Polynomial Y = -7.789x2 + x – 7249.549 12.400 3.467

NO2 -0.650 0.432 Polynomial Y = -0.858x2 + 51.668x – 700.434 7.667 3.467

The traffic volume is one of the characteristics of

traffic that can affect the pollutant concentration in the

ambient roadside (Bachtiar et al., 2016a; Bachtiar et al.,

2017.) Based on Figure-2 and Figure-5,it shows that the

concentration of CO and NO2 have the similar pattern with

the traffic volume, which increased traffic volume will be

followed by increasing concentrations of CO and NO2 and

vice versa. While concentrations of O3 has a different

pattern to the traffic volume, it is because of O3 is a

secondary pollutant which concentration changes every

hour and tend to be more affected by solar radiation and

surface temperatures. According to Ahammed et al., 2006,

O3 are influenced by meteorological parameters like wind

speed, wind direction, temperature and relative humidity.

Statistical test relations of O3, CO and NO2 with

tthe volume of traffic can be seen in Table-3. Based on

this table, relations between concentrations of O3, CO and

NO2 with the volume of traffic at three locations show that

correlation values (r) is positive, with interpretation of

relations quite diverse ranging from strong enough, strong

and very strong.

01002003004005006007008009001000

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(µ

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3)

O3

, N

O2

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te

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era

ture

(oC

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Table-3.Statistical test relations of O3, CO dan NO2 concentrations with traffic volume.




O3 0.671 0.450 Exponential Y = 33.612e0.000x

18.035 4.301

CO 0.968 0.937 Exponential Y = 119.695e0.001x

325.644 4.301

NO2 0.435 0.189 Logarithmic Y = 3.048 ln(x) + 16.487 5.141 4.301



19.934 4.301


415.936 4.301

NO2 0.508 0.258 Polynomial Y = 4.040E-6x2– 0.001x + 44.444 3.648 3.467



17.780 4.301


157.699 4.301

NO2 0.691 0.477 Polynomial Y = 1.185E-5x2 - 0.022x + 58.977 9.578 3.467

The increase in the growth rate of vehicles will

lower the average speed of vehicles on the highway.

Traffic speed will affect the amount emitted by the

vehicle. Statistical test relations of O3, CO and NO2

concentrations with the speed of traffic can be seen in

Table-4. Based on Table-4, relations of O3, CO and NO2

with the traffic speeds at the three locations show that

correlation values (r) is negative, with interpretation of

relations is quite diverse ranging from the weak, strong

enough, strong and very strong.

Table-4. Statistical test relations of O3, CO dan NO2 concentrations with traffic speed.




O3 -0.411 0.169 Exponential Y = 65.048e-0.01x

4.901 4.301

CO -0.619 0.384 Exponential Y = 1221.332e-0.042x

13.692 4.301

NO2 -0.293 0.086 Exponential Y = 48.900e-0.009x

2.061 4.301



5.370 4.301


36.124 4.301

NO2 -0.364 0.132 Polynomial Y = -0.048x2 + 2.543x + 28.371 5.861 3.467



10.311 4.301


42.360 4.301

NO2 -0.567 0.322 Polynomial Y = 0.039x2 – 4.318x + 171.076 4.980 3.467

Based on Table-4, NO2 has a correlation value (r)

which is relatively weak. It shows that the effect of the

traffic speeds on variations in the concentration of NO2 in

the three research location is relatively small.The

relationship between the concentrations of O3, CO and

NO2 with traffic density, as well as the volume of traffic.

Traffic density is directly proportional to the concentration

of O3, CO and NO2, it is seen from Figures4 and 5.Based

on statistical test of relations between the concentrations

of O3, CO and NO2 with traffic density at three locations

show that correlation values (r) is positive, with the

interpretation of relations quite diverse ranging from

strong enough, strong and very strong. Relations of O3,

CO and NO2 concentrations with traffic density are shown

in Table-5.




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Table-5. Statistical test relations of O3, CO and NO2 concentrations with traffic density.


r R2 Type of Regression Regression Formula Fvalue Fcritical value



14.002 4.301


349.909 4.301

NO2 0.444 0.197 Logarithmic Y = 2.834 ln(x) + 28.064 5.388 4.301



16.613 4.301


285.533 4.301

NO2 0.487 0.237 Linear Y = 0.311x + 41.560 6.831 4.301


O3 0.680 0.462 Polynomial Y = -0.014x2 + 2.165x + 6.808 9.013 3.467


83.577 4.301

NO2 0.682 0.465 Polynomial Y = 0.004x2 + 0.002x + 50.979 9.127 3.467

CONCLUSIONS

Concentration of O3, CO and NO2 in the three

research location are still below the quality standard,

according to the National Quality Standard. Diurnal

variation pattern of O3 concentrations tend to start

increasing from morning until noon, then in the afternoon

until night decreased. While diurnal variation pattern of

concentration of ozone precursors, CO and NO2, increased

in the morning and evening, while in the daytime and

nighttime concentrations decreased.

The increase of solar radiation and the surface

temperature is directly proportional to the increasing of

concentrations of O3 and inversely proportional to the

concentration of ozone precursors (CO and NO2).

The increasingof volume and traffic density is in

line to increasing concentrations of O3, CO and NO2,

while the traffic speeds is inversely proportional to the

concentration of O3, CO and NO2.

ACKNOWLEDGEMENT This study was funded by Environmental

Engineering Department, Andalas University, Year 2016.

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diurnal variation of tropospheric ozone (o3 ... · bureau of statistics of padang city (2015) noted...

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