vehicular pollution estimation on g.t. road

8/13/2019 Vehicular Pollution Estimation on G.T. Road.

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CHAPTER 1

INTRODUCTION

1.1. General:

Air pollution has been aggravated by developments that typically occur as

countries become industrialized: growing cities, increasing traffic, rapideconomic development and industrialization, and higher levels of energy

consumption. The high influxes of population to urban areas, increase in

consumption patterns and unplanned urban and industrial development have

led to the problem of air pollution. Motor vehicular usage has increased

tremendously across the World. In 1950 there were 53 million cars on roads of

the World which increased to 500 million by the year 2000. The situation in

Pakistan is not different from rest of the World. About 4.3 million vehicles are

plying on the roads of Pakistan (Aziz, 2009). According to Pakistan

Environment Protection Agency, in Pakistan number of vehicles has jumped

from 0.8 million to 4.0 million during last 20 years showing an overall

increase of more than 400 percent. The average compound growth of vehicles

is about 11 percent per annum. The road Length, which was about 94000 l ip

in 1980-81, increased to 232000 m in M7-98 indicating an overall increase of

1 47 percent. Driving forces behind high growth of vehicles are population

explosion, gigantic expansion of cities, GDP and household income rise,

inconsistent mass transit system, car financing schemes and change in landuse

policy popularly known as commercialization policy. At the time of

independence in 1947, 32.5 million people lived in Pakistan. The population

of Pakistan is estimated as 160 million in 2007 with an average growth rate of2.6 percent per annum. An estimated time for doubling of population in


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Pakistan is 24 years whereas such doubling occurs in America, Canada and

Japan in 100 years, 233 years and 350 years respectively.

1.2. Study area:

Grand Trunk (GT) Road, on of the busiest and famous road of Pakistan was

built by Pashtun emperor Sher Shah Suri in 16 th century in order to link

together the remote provinces of his empire. The study reach is a stretch of

about 3.3km of N5 (AH 1) GT Road between Co-operative Store intersection

and Shalimar intersection. The figure 1 shows the road section which was

studied.

Figure 1.1: Study Area of G.T. Road between Co-operative Store intersection and Shalimar

intersection.


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1.3. Problem statement:The rapid growth in motor vehicle activity in cities of Pakistan has brought in its

wake a range of serious socioeconomic, environmental, health, and welfare

impacts. Of these impacts, those resulting from urban air pollution, due to

emissions from motor vehicles among other sources, have been the focus of

considerable public concern and policy attention. In Delhi, for example, air

quality has been poor since the late 1980s. Surveys in the mid-1990s showed 24-hr average suspended particulate levels exceeding World Health Organization

(WHO) guideline limits almost daily, with peak levels as high as 6 10 times the

limit at many sites. Daily average sulfur dioxide and nitrogen dioxide levels

exceeded WHO limits on several days annually, at several sites. Ozone has not

been monitored regularly, but limited studies in the 1990s showed that short-term

WHO limits were exceeded at some locations (Environment Protection AgencyPakistan, 2004). Table 2 contains recent data that show that 24-hr particulate

limits continue to be exceeded even in residential areas. Such high air pollution

levels occur in Karachi and other major cities of Pakistan, because of the

concentration of motor vehicular and other energy-consuming activities in these

cities and the high pollution intensity of these activities. And because of the large

populations in these cities, significant exposures and health impacts result.

Table 1.1: Motor vehicle growth in Pakistan, 1975 2005. (Ilyas, 2009)

Year Trucks Buses Jeep, Cars & taxis M2Wvehicles

*Others Total motorvehicles

1975 0.22 0.05 0.280 0.05 0.11 0.711985 0.6 0.16 0.86 0.28 0.192 2.0921995 3.5 1.32 3.6 6.3 1.2 15.922005 4 2.1 8.29 20.50 2.7 37.59

(Motor vehicle numbers, millions)

*Others: includes tractors, trailers, M3W vehicles, and miscellaneous vehicles not

separately classified. M2W motorized two-/three-wheeler vehicles.


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1.6. Limitations:

Due to the limited resources and time, the study is primarily focused uponvehicular emission of only 3.3km road. The other limitations are;

Only two intersections were studied. Emission factors are not authentic as they have been taken from Indians

Vehicle research.

Only 2 hours traffic count was performed for two days.

Model calibration and verification is not studied as air sampling procedures are not adopted.


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CHAPTER 2

LITERATURE REVIEW

Air pollution is the presence of one or more contaminants in the outer

atmosphere, of quantities, of characteristics and for such a duration that is

harmful to human health, animals, plans and property. It significantly reduces the

enjoyment of life and property. There are different sources of air pollution the

major concern here is vehicular pollution.

2.1. Major air pollutants:

The air pollutants that are of major concern are as follows;

Particulate Matter Carbon Monoxide Nitrogen Oxides Sulfur Dioxide Lead Ozone

2.2. Vehicular Pollution:

The emissions from automobile are of major concern in urban setting due to high

levels of pollution. The sources of pollution in automobile are;

Exhaust gases. Fuel tank emissions.

Evaporation from carburetor.

In order to measure the pollutant quantities there are some factors to be consider

like Roadway characteristics, traffic loads, fuel, condition of vehicles etc.


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Table 2.1: Sectorial oil Consumption 2000-1: Total 19.35 Million Tons

Sector % age Transport 46.2Power 36.8Industry 10.9Domestic 2.6Other Govt. 2.1Agriculture 1.4

(Source : CNG Sub-Sector by Hilal A Raza, DG, and HDIP on Jan, 11 th 2002 A presentation to

the Task Force on Integrated Energy Security Action Plan.)

The comparison of Petrol and Diesel vehicle emission (expressed as lb/1000

Gallons fuel burnt) is given in the table below;

Table 2.2 : Comparison of pollutant emitted from Diesel and Petrol Vehicles.

Pollutant Diesel Petrol

Aldehyde (HCOH) 10 4

CO 60 2300

HC 136 200

NO x 222 113

SO x 40 9

Particulates 110 12

2.3. Roadway Characteristics:

Characteristics of a roadway has a correlation with vehicular emissions, the

characteristics included are as follows;

Signal timings. Number of speed breakers or humps. Idling time of motor vehicles at intersection and at signal. Traffic load.


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Number of U-turns. Road roughness, rutting and fatigue cracking. On-site parking.

Road infrastructure like, shoulders, camber, median, lanes, markings, islands,

zebra-crossing, curbs, green belts, traffic signals, bus stop, overhead

pedestrian bridge, side walk etc.

2.4.

Pollution Load Estimation:There are two methods used for this purpose which are as follows;

i. Sampling & analysis of pollutants from source.

ii. Emission factor models.

2.5. Emission Factor:

It is a representative value that relates the quantity of a pollutant released to the

atmosphere with an activity associated with the release of that pollutant. It is

expressed as weight of pollutan t per unit weight, volume, distance, or duration of

the activity emitting the pollutant. Emission factors vary with type of vehicle,

type of fuel. Different countries have different emission factors, but generally,

(Emission) pollutant = (Activity) * (Emission Factor) pollutant

2.5.1. Parameters affecting Emission Factors

The parameters that affect the emission factor values are as follows;

Vehicle/Fuel Characteristics Fuel quality Operating Characteristics Vehicle age and mileage accumulation


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Driving mode and engine load Maintenance and tampering

Higher average temperatures, Poor fuel quality, Poor vehicle maintenance culture,

more the load of old vehicles , Higher Value of Emission Factor

2.6. Models based on Emission factors:

There are difference models developed by USEPA based on Emission factors, which are

as follows;

EETM. CHEM. EMFAC.

2.7. Gaussian Plume Dispersion Model:

Plume is the continuous remittance of smoke from a stack or solid waste disposal

point, or in our case we have considered our road as a plume source as motor

vehicles are continuously plying on the road. The mathematical expression of

Gaussian Plume Model is as follows;


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Figure 2.1 : Gaussian Plume Dispersion Model.

2.8. Metrological factors and air pollution dispersion:

Metrology is scientific study of the Earths atmosphere. It is basically the study of

weather. Metrological factors affect the air pollution concentrations at a place.

Factors which are of prime concern are;

Wind. Temperature. Precipitation.

The motion of causes a dilution of air pollutants. Similarly temperature helps in

vertical dispersion of pollutants. Lower wind and lower temperature clamps the

pollutants upon the communities where they are produced and result in high

concentration build up.

2.9. Wind rose:Meteorologists use a graphical representation called wind rose to represent wind

speed and direction over the period of time and at a specific location. Wind speed

and direction is important while predicting the dispersion of pollutants. Most

commonly 16 directions are there. The wind rose of Lahore (2008) are shown in

the figure below;


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Windrose Summer/Monsoon (Jul-Oct)

0

0

3

1.5

6

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10

5.1

16

8.2

(knots)

(m/s)

Wind speed

0 1020

30

40

50

60

70

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90

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110

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130

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160170180190

200

210

220

230

240

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260

270

280

290

300

310

320

330

340350

100

200

300

400

Figure 2.4: Wind Rose for the Summer ( MAR-JUNE) 2008, Lahore

Figure 2.5: Wind Rose for the Summer/ Moon soon (July-OCT)

Wind direction is always defined as that from which the wind is blowing, i.e. a

north wind comes from north. The position of spoke shows the direction from

which the wind was blowing. The thickness of spoke shows the wind speed and

its lengths shows percentage of time the wind was blowing from that direction.

Windrose Summer (Mar- Jun)

0

0

3

1.5

6

3.1

10

5.1

16

8.2

(knots)

(m/s)

Wind speed

0 1020

30

40

50

60

70

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90

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160170180190

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310

320

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340350

100

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400


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Table 2.3: Wind Speed, Humidity, Pressure, Temperature and Direction 2012

Ambient

Temperature

Wind

Direction

Wind Speed Humidity Pressure

oC m/s % (mm of Hg)

29 SW 4.9 40 756.1

29 SE 3.6 55 756.9

31 SE 4.0 51 756.6

29 N 0.9 44 756.0

28 N 0.4 58 757.0

25 N 0.4 71 757.3

24 N 0.4 73 757.7

23 N 0.4 79 758.1

22 N 0.4 85 758.0

21 N 0.4 89 758.3

22 N 0.9 85 758.3

21 N 0.0 91 758.7

20 E 2.2 97 757.7

20 E 0.9 99 758.0

19 S 1.8 99 758.6

19 S 2.2 99 759.5

20 E 0.9 99 760.5

22 NE 0.4 95 760.1

25 NE 4.0 76 760.4

27 E 3.6 59 760.8

28 E 3.1 52 760.8

26 SE 3.1 62 760.3

It is evident from the wind rose of Lahore that most of the times the wind blows

from North-West to South-East. Furthermore the average wind speed was 3m/s

for most of the time.


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CHAPTER 3

MATERIALS AND METHODS:This chapter presents the methods and techniques used for this work. Detailed

survey was carried out and following data were collected.

3.1. Roadway Characteristics:

Typical Cross-section of roadway is given below;

Figure 3.1: Typical cross section of a road way.

Table 3.1: Cross-sectional dimensions of GT-Road near UET,Lahore.

Cross-sectional elements Dimensions

Side walk 8ft

Green belt 26ft 3in

Shoulder 2ft 6in

Travel way 47ft

Shoulder 1ft 6in

Median 4ft

Shoulder 1ft 3in

Travel way 46ft

Shoulder 3ft 9in

Green belt 39ft

Side walk 10ft 8in


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3.2. Signal timings:

The study reach involve two intersections I.e., Co-operative Store Intersectionand Shalimar Intersection. The signal time presented in the table below;

Table 3.2: Signal timing within the given length of road.

Signal color Signal Time (minute)

At signal on AFC lane

Green 1:42

Red 1:08At signal on UET lane near Govt. High school Shalimar.

Green 1:56

Red 1:23

3.2.1. Miscellaneous features of the study area:

The given length of road has following features;

The oldest Engineering University of Pakistan, i.e., University of

Engineering & Technology is situated on GT-Road.

The famous Shalimar Garden is situated on GT-Road. Lahore Science museum is on GT-Road. Schools and 5 petrol pumps, 2 old tomb and mosques. KFC, AFC, Gourmet bakery, several motor bike workshops, fruit vendors. It has 1 over-head pedestrian bridge and 10 U-Turns.

3.3. Traffic count survey:

The traffic count survey was performed on GT-Road was scheduled as given in

the table below;


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Table 3.3 : Schedule for traffic count survey.

Date Time Status

Dec 5, 2013 1:30pm to 2:30pm Peak Hour

Dec 7, 2013 10:00m to 11:00am Normal Hour

The locations selected are given in the figure below;

Figure 3.1: Survey locations (red triangles perpendicular to road)

The 4 survey locations that selected are as follows; In front of AFC, PHA, School

at Shalimar, show-room opposite to school. The figure below shows the surveyors

that were performing the traffic count survey. The Performa used for the traffic

count purpose is attached in Annexure I.


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Figure3.2: Surveyors standing in front of AFC and PHA (from left to right)

3.4. Emission factors:

As described in Chapter 1, limitations of this work, the emission factors for

different countries are different. Here, the emission factors that were adopted

from Indians research work. The reason behind this was that the socio -economic

conditions vehicle types etc. of India and Pakistan are to some extent similar. The

adopted emission factors are as follows;

Table 3.4: Emission factors based on engine capacity.

Engine Capacity Emission Factor (g/km) Emission Factor(mg/km)

Cc CO HC Nox CO2 PM TotalAldehyde

TotalPHM

70 1.65 0.61 0.27 24.97 0.037 0.01 1.5752150 5.1 2.46 0.01 25.05 0.073 0.0044 0.0012

200 1 0.26 0.5 77.7 0.015 0.0085 0.4035660 4.53 0.66 0.75 106.96 0.008 0.6195 0.1428800 4.53 0.66 0.75 106.96 0.008 0.6195 0.1428

1000 4.53 0.66 0.75 106.96 0.008 0.6195 0.1428

1300 3.01 0.19 0.12 126.56 0.006 0.0079 0.13241600 0.87 0.22 0.45 129.09 0.145 0.0813 0.10142600 0.39 0.1 0.62 216.75 0.01 0.019 0.3153

3000 3 1.28 2.48 333.31 0.655 0.2169 3.7742

3500 3.07 2.28 3.03 327.29 0.998 0.2957 8.1284

Models used here was EETM model and Gaussian Plume dispersion Model.


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CHAPTER 4

POLLUTION LOAD ASSESMENT

This chapter presents the results of the vehicular pollution load and the

comparison of peak and normal hour concentrations along with different types of

vehicles. During survey the pollution that was observed is shown in the figures

below,

Figure 4.1: pollution status on GT-Road Lahore.


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The table below presents the total number of vehicle cunted.

Table 4.1:; TOTAL TRAFFIC ON 3.3 KM G.T ROAD REACH

PEAK HOURS EngineCapacity

Peak

Hour

Normal

HourType of vehicle ccMotor Cycle +Chingchi

70 6099 5193

Accord 3000 1 3

Alto 1000 35 40

Auto 200 1025 602

Beleno 1300 15 9Belta 1300 3 3

Centro 1000 18 30

Charade 1300 6 17

City 1300 100 37

Civic 1600 24 17

Corolla 1600 139 99

Cultus 1000 104 80

Cuore 800 47 41Fx 800 5 6

Khyber 1000 4 18

Lancer 1300 3 21

Landcruiser 3500 67 15

Liana 1300 4 12

Mehran 800 114 127

Minicars 660 382 144

Mira 660 4 9

Nissan 1300 3 31

pick up loader 1600 530 2

Platz 1300 5 10

Probox 1300 1 6

Rush 660 7 15

Scooter 150 7 12

Swift 1300 20 1

Vigo 2600 3 17

Vitz 1000 25 6


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4.1. EETM Model results:

EETM model was used in order to estimate the pollution loads, the resultsobtained are as follows;

Table 4.2: Comparison of Pollutant emission during different time duration.

Pollutant PeakConc.

(kg/day)

NormalConc.

(kg/day)Peak conc.(tons/year)

Normalconc.(tons/year)

C0 52.11779 40.1806 19.02299 14.66592

HC 15.94893 12.50027 5.821361 4.562598Nox 10.74629 7.34052 3.922394 2.67929CO2 1466.573 908.7129 535.2991 331.6802PM 1.374467 0.796198 0.50168 0.290612Total Aldehyde 0.00201 0.001297 0.000733 0.000473Total PHM 0.035534 0.0286 0.01297 0.010439

0

100

200

300

400

500

600

Comparison of yearly Normal and Peak hour

concentrations.

Peak conc.(tons/year)


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Table 4.3 : Comparison of different types of vehicular emissions/

Vehicletype

Cars Cingchi+bikes Auto rickshaw

Pollutant Peak Conc.(kg/day)

Normal Conc.(kg/day)

Peak Conc.(kg/day)

Normal Conc.(kg/day)

Peak Conc.(kg/day)

NormalConc.

(kg/day)C0 15.40843 9.716157 33.2 28.275 3.38 1.98

HC 2.73537 1.432827 12.3 10.45 0.879 0.516Nox 3.620595 1.719861 5.4 4.626 1.69 0.9933CO2 700.6103 325.4537 502.5 427.9 262.8 154.358PM 0.577355 0.129443 0.744 0.634 0.05 0.02979TotalAldehyde

0.001779 0.001108 0.0002 0.000171 2.79E-05 1.69E-05

TotalPHM

0.002466 0.000804 0.0317 0.02699 0.0013 0.000802

0

200

400

600

800

1000

1200

1400

1600

Comparison of daily Normal and Peak hourconcentrations.

Peak Conc. (kg/day)

Normal Conc. (kg/day)


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Table 4.4: Comparison of pollutant concentrations in terms of tons/year.

Vehicle type Cars Cingchi+bikes Auto rickshaw

Pollutant Peak conc.(tons/year)

Normalconc.

(tons/year)


Normalconc.

(tons/year)


Normalconc.

(tons/year)C0 5.624075 3.546397 12.118 10.32038 1.2337 0.7227

HC 0.99841 0.522982 4.4895 3.81425 0.320835 0.18834Nox 1.321517 0.627749 1.971 1.68849 0.61685 0.362555CO2 255.7228 118.7906 183.4125 156.1835 95.922 56.34067PM 0.210735 0.047247 0.27156 0.23141 0.01825 0.010873TotalAldehyde

0.000649 0.000405 0.000073 6.24E-05 1.02E-05 6.17E-06

Total PHM 0.0009 0.000294 0.011571 0.009851 0.000475 0.000293

0

100

200

300

400

500

600

700

800

Comparison of daily emission conc. from different types of vehicle.

Cars Peak Conc. (kg/day)

Cars Normal Conc. (kg/day)

Cingchi+bikes Peak Conc.(kg/day)

Cingchi+bikes Normal Conc.

(kg/day)Auto rickshaw Peak Conc.(kg/day)

Auto rickshaw Normal Conc.(kg/day)


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0

50

100

150

200

250

300

Comparison of yearly emission conc. from different types ofvehicle.

Cars Peak conc. (tons/year)

Cars Normal conc. (tons.year)

Cingchi+bikes Peak conc.(tons/year)

Cingchi+bikes Normal conc.(tons.year)

Auto rickshaw Peak conc.(tons/year)

Auto rickshaw Normal conc.(tons.year)

0

200400

600

800

1000

1200

1400

1600

Comparison of daily Normal and Peak hour concentrations from

cars

Peak Conc. (kg/day)

Normal Conc. (kg/day)


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Fruit venors were along the road, and if these fruits are being consumed without

proper washing it may be a sort of health hazard.

Observed traffic load can cause damage to plant photosynthesis and other

impacts on plants and buildings

Figure 4.3: Traffic situation along the road.


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CHAPTER 5

ON-ROAD VEHICULAR POLLUTION

DISPERSION MODELLING

Gaussian model was used in order to estimate the zone of impact and

concentration of plume on ground. The following assumptions were taken. Average ambient air temperature is 25 0C. The average wind speed is considered as 3m/s (Reference: NESPAK,

2008)

The average diffusion co-efficient in horizontal and vertical dilution

under normal stability conditions were taken as 70 and 50m respectively.

The results obtained are as follows;Table 5.1: Night time concentrations

Distance(km)

Concentration at respective distance (ug/m3)

CO HC NO x CO 2 PM

1 7.604566 2.337886 6.90752E-05 0.009204 8.49304E-06

2 1.390595 0.427513 1.26313E-05 0.001683 1.55306E-06

40.492889 0.15153 4.4771E-06 0.000597 5.50475E-07

5 0.271814 0.083564 2.46899E-06 0.000329 3.03571E-07

7 0.157305 0.048361 1.42886E-06 0.00019 1.75683E-07

9 0.126743 0.038965 1.15125E-06 0.000153 1.41551E-07

10 7.604566 2.337886 6.90752E-05 0.009204 8.49304E-06

5.1. Wind rose and dispersion patter:

As wind rose of Lahore suggests that the wind direction is from NW to SE most

of the time so the pollution will disperse accordingly. As U.E.T. and Shalimar


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garden located in North East the dispersion of pollution also divert towards the

these places as NE wind in Lahore is dominant after SE & NW winds.

Figure 5.1 : Wind Rose of Lahore, 2008 NESPAK.

0

100

200300

400

500

600

700

800

900

1000

N NE E SE S SW W NW

15 and above

12-14.9

9-11.9

6-8.9

3-5.9

0-2.9

F r e q u e n c y

i n h

r s


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CHAPTER 6

CONCLUSION & RECOMMENDATIONS

Automobiles are large contributor to the environmental pollution. The different

fuel consumption and air pollution models discussed in this report help us to

estimate how much fuel we are using and the amount of pollutants we are

releasing in the atmosphere. As the population and number of vehicles are

increasing abruptly, more amounts of pollutants are being discharged. If this trend

continues, there will not be any more energy sources left for the future

generations. Also, the world will be so polluted that living organisms may not be

able to thrive. Hence, we need to understand the importance of saving the

environment. Alternate sources of fuels for e.g. renewable sources can be used

which also help in reducing the pollution. Our aim must be to preserve the nature

and have the environment, along with a sustainable transportation system.

Recommendations:

An integrated Transport policy need to be announced and route

rationalization strategy for introduction and operation of public transport

is to be made necessary. Financial earning at cost of environment should stop immediately. Hence

forth commercialization policy needs to be withdrawn. Requirement for

change in landuse may be met through spatial planning which is now

mandatory function of City District Government Lahore.

Environment protection may be included among kernel functions of City

District Government Lahore and therefore sway under separate EDO (

Executive District Officer)

Organizational setup as proposed in Devolution Plan 2001 may be

adopted to achieve optimum harmony among key tiers of transportation

and environment protection


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To ease congestion within City Circular railway around city has to be

setup.

To reduce congestion, scope and management of bus transit lane is to be

thrash out at major roads of city. It not only creates a feeling of superiority

among passengers but also helps in reducing unrelenting trend of

motorization

Role of decentralized environment Department of City District

Government Lahore is required

Use of catalytic converter for motor vehicles. Use of alternate fuels. Proper road traffic planning. Introduction pf public transport. Proper maintenance of motor vehicles.


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Annexure I:

Traffic survey Performa:

Type of vehicleMotor Cycle + ChingchiAccordAltoAutoBelenoBeltaCentroCharadeCityCivicCorollaCultusCuore

FxKhyberLancerLandcruiserLianaMehranMinicarsMiraNissanpick up loaderPlatzProboxRushScooterSwiftVigoVitz

vehicular pollution estimation on g.t. road

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