Home Articles Environmental Effects of Urban Traffic – A case study of Jaipur City

Environmental Effects of Urban Traffic – A case study of Jaipur City

Sandeep Maithani, B S Sokhi and A P Subudhi
Human Settlement Analysis Group,
Indian Institute of Remote Sensing, Dehra Dun, India
[email protected]

K B Herath
Survey Department of Sri Lanka,
Sri Lanka

Growing Urban centres necessitate the sprawling of transportation network, increasing distance between places of residence and work which needs to be covered in minimum time. The increased socio-economic status of urban population coupled with inadequacy of public transport has encouraged personalized means of transport. This craze for owning vehicles in urban centres, has led to considerable noise and air pollution, especially in big cities. (Table 1)
Table 1. Noise levels in major Indian cities

City Day Night
Delhi 83 dB 77dB
Calcutta 82dB 75dB
Bombay 80dB 71dB
Madras 77dB 73dB

  • Acceptable noise level is 50dB as prescribed by Ministry of Environment and Forests (1989)
  • dB stands for Decibel

Jaipur, which is one of the twenty three metropolitan cities in India, with a population growth rate of 49% per decade, is also encountering similar problems. The city besides being the capital of Rajasthan state is also a major tourist centreof the country. The city has developed in a rather imbalanced form. While most of the economic activities are located in the walled city area, the residential colonies are growing in western and southern parts, which are far off from the walled city (the main centreof activities). This imbalance in the location of jobs and residences over space coupled with inadequacy of public transport system generates huge volumes of intermediate and personalized traffic especially on arterial roads, with growth rates of traffic volumes ranging between 6-12% per annum. The objective of this paper is to model the effects of urban traffic on environment in terms of population affected by air and noise pollution, using predictive and dispersion models, in a GIS environment with inputs from remote sensing. The major arterial roads in Jaipur have been considered in this study.

Study Area
Jaipur is the second largest city in Rajasthan. It is located between 26°48’15″ to 27°00’15″N latitude and 75°41’15″ to 75°53’45″E longitude, covering an area of 350 km² with 70 municipal wards. The population of the city was 1,518,235 in 1991 as per census and 2,536,669 according to a study carried out by UNICEF in 1997. The city falls within semi arid climatic zone with an annual rainfall of 60 cm. The urban area and its hinterland are mainly covered with thick mantle of soil, wind blown sand and alluvium. The eastern and northen parts are formed of Aravali hill ranges.

Considering the development status, the physical development can be categorized into two parts (i) Walled city area (ii) Outside walled city area. The walled city area is conventionally developed area having densely populated residential and commercial landuses with no scope for physical expansion. This has pressurized development in the southern and western side (as physical constraints are imposed by Aravali ranges in the north and east side of city). To serve these areas the road network has been extended.

The main arterial roads considered in this study are:

  • J.L.N Marg, , New Sangner Road, Tonk Road, and in the south.
  • Nirman Marg, M.I Road, Hawa Sarak and Amer Road in the north.
  • Ajmer Road, Khatipura Road and Jhotwara Road in the west.
  • Agra road and Jhalana Dungri Road in the east.

Table 2. Example of Air pollution dataset

Road Name SPM* SOX NOX COX Ammonia
M.I.Road 471 7 19 20 35
Jhotwara Road 296 11 12 17 26
J.L.N Road 311 6 13 15 24

All units are in mg/m3

  • *Suspended Particulate Matter
  • For SPM the frequency is 24 Hourly, 10days/month, annual mean
  • For SOX , NOX , COX , Ammonia the frequency is 4 Hourly,

10 days/month, annual mean
Table 3 : Buffer Zones of Air Pollution

0-425 METRE SOX , NOX , COX , Ammonia and Suspended particulate matter

Data Used and Methodology
The Survey of India topographical sheets (45N/13 and 45N/9 ) surveyed in 1971 on 1:50,000 scale and guide map of Jaipur city on 1:25,000 scale surveyed in 1971 were used for preparing the base maps. IRS-1C geocoded LISS-III FCC of 14 April 1998 on 1:50,000 scale and IRS-1C geocoded PAN data of 12 March 1998 on 1:25,000 scale were visually interpreted for making the existing landuse and arterial road network map (Figure 1 & 2) Field verification survey was carried out to check the interpretation accuracy and to collect secondary data on traffic, pollution and population density (Figure 3). The maps were digitized and incorporated within GIS domain (ArcInfo and ILWIS ), for creating thematic layers like landuse, road network, ward-wise population density and calculating length of roads and areas of various landuses.’

Figure 1: Landuse map of jaipur 1998

Figure 2: Transportation network jaipur city
For the purpose of analysis ward-wise population density maps were crossed with catchment areas (based on models) of environmental parameters (air and noise pollution), to find population affected by each environmental parameter.

Figure 3: Ward wise population density jaipur city

Air Pollution Dispersion model
The main pollutants from automobile exhaust are oxides of nitrogen, sulphur, carbon ( NOX, SOX, COX resp.), ammonia and suspended particulate matter. At the roadside the concentration is highest while it decreases away from the road. For each pollutant a buffer zone was calculated within which concentration of pollutant exceeds air standard limits.
Table 4. Example of Noise Pollution Dataset

Road Name Volume of traffic 12 hours (8A.M –8P.M) Average vehicle speed (Km/h)
M.I.Road 64281 24
Jhotwara Road 43278 30
J.L.N Road 34537 45

Table 5 : Buffer Zones of Air Pollution


Buffer zones were calculated based on Passquill and Smith (1983) dispersion model and using data sets (an example of dataset used is shown in Table 2)

C (x,z) = [(2Q/L)/ ((2p)½ usz)] exp (-z2/2s2z) …………. (Eq.1)
Q/L = Emission per unit length of road (mg/second metre)
sz = Gaussian coefficient for vertical dispersion (metre)
u = Mean wind speed (metre / second)
C = concentration of pollutant (mg/metre3)

The two buffer zones calculated were:

  • 425 metres on either sides of arterial roads
  • 1500 metres on either sides of arterial roads

After the 425 metre buffer zone the concentration of SOX, NOX, COX, Ammonia was within acceptable limits. Therefore in 0-425 metre zone population is affected by SOX, NOX, COX, Ammonia and Suspended particulate matter. While in the 425-1500 metre zone, the population was affected by Suspended particulate matter, so the buffer zones used in the analysis were (Table 3).

Noise Level Prediction Level
Noise can be defined as unwanted sound in the wrong place at the wrong time. The highway noise prediction model used in this study (Lyons, 1973) is based on the principal: Noise is produced by traffic and is then attenuated by distance before it reaches the listener. The noise level can be well predicted using Lyons empirical model:

L = 10logV – 15logD + 30 logS + 10log[tanh (1.19*10-3 )* VD/S] + 29 ……..(Eq.2)

V= Volume of Traffic per hour (vehicles/hour)
S= Average vehicle speed (miles/hour)
D = Distance from centreline of road to sound receptor (feet)
L= Predicted noise level (dB)

Keeping in view the acceptable noise level of 50 dB (as prescribed by the Ministry of Environment and Forests 1989) two buffer zones were calculated (Table 5) using Eq.2 and data sets (an example of dataset used is shown in Table 3).
Table 6 : Population affected by air pollution in Jaipur city (Figure 4)

(52.7 % of total population)
(41.6% of total population)
(94.3% of total population)

Table 7 : Population affected by noise pollution in Jaipur city (Figure 5)

(2.3 % of total population)
(32.6% of total population)
(34.8% of total population)

These buffers zones layers were overlaid on the population density layer to find out the population affected by these two pollutants. The affected population is shown in table 7.

Figure 4: Air pollution bufer zones

Figure 5: Noise pollution bufer zones
Results and Discussion
It was found that significant numbers of population were affected by air and noise pollution (94.3% and 34.8% of total population respectively). 52.7% of total population lying in 0-425 m buffer zone was affected by all air pollutants and 41.6% of total population lying in 425-1500 m buffer zone was affected only by suspended particulate matter only.

2.3% of total population lying in 0-30 m buffer zone was affected by noise pollution, the minimum noise level being 60 dB and 32.6% of total population lying in 30-250 m buffer zone was subjected to noise level ranging from 50-60 dB.

Thus, 2.3% of total population (57,587) was subjected to maximum air and noise pollution. With increasing vehicular traffic the impact of noise and air pollution would increase within this buffer zone (0-30 m) on the existing population.

The maximum intensity of noise and air pollution was recorded at Hawa Sarak, M.I.Road and Jhotwara Road . The high intensities of pollution in above-mentioned roads was mainly due to connection of these roads directly to commercial areas, industrial areas and offices. J.L.N. Marg where the Rajasthan University is located, is also having high intensity of pollution during office hours because this is the only road linking the residential areas with the state and central offices and business centres. Agra Road is also having high intensity of pollution since it carries heavy inter-state traffic.

The ‘KHAT’ coefficient calculated after field survey for measuring classification accuracy was 85.8% therefore proving that remote sensing data can be used for providing spatial information for Environment Impact Studies.


  • The travel projected for 2011 shows corridors of heavy volume in the north-south and east-west direction, so there is a urgent need for an alternative public transport system on identified roads, to reduce air and noise pollution as well as to reduce the growth of personalized modes of transport.
  • The Jaipur development authority should shift some commercial activities to other parts of the city.
  • GIS along with input from remote sensing can be used to calculate catchment areas and population affected by pollution, quickly and accurately as compared to conventional methods.
  • Planting of trees on both sides of roads as well on as on central verge, strict adherence to pollution standards is needed to reduce pollution .

The authors are grateful to Dr P S Roy , Dean, Indian Institute of Remote Sensing for providing all necessary help and guidance during the work.


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