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Impact Assessment of Traffic Noise in a Densely Populated Industrial City, Faisalabad Pakistan Using Geostatistical Approach and Development of Sustainable Transportation System Framework

Impact Assessment of Traffic Noise in a Densely Populated Industrial City, Faisalabad Pakistan... GEOLOGY, ECOLOGY, AND LANDSCAPES INWASCON https://doi.org/10.1080/24749508.2021.2022575 RESEARCH ARTICLE Impact Assessment of Traffic Noise in a Densely Populated Industrial City, Faisalabad Pakistan Using Geostatistical Approach and Development of Sustainable Transportation System Framework Sehrish Latif, Haroon Rashid and Abdul Nasir Department of Structures & Environmental Engineering, University of Agriculture, Faisalabad, Pakistan ABSTRACT ARTICLE HISTORY Received 1 March 2021 Haphazard and noisy traffic in congested and densely populated old cities has become Accepted 7 October 2021 a challenge for the environmental and transportation engineers to provide better means of transportation with raised quality of life and environment. Faisalabad is an old and major KEYWORDS industrial city of Pakistan, which has huge influx of population due to its industrial significance. Sustainable transportation It has been facing severe traffic issues, which result in a noisy and irritating environment all system; noise pollution; around. This research work was planned to find out the health impact of noisy traffic on the haphazard traffic; heavy residents and their social life, determining noise level variation trends with the changing traffic; geostatistical analysis; health impact density of traffic at different time intervals in a day and how variations occur during different weekdays. This study was focused to enquire the severity of noise levels due to road traffic with reference to significant selected locations throughout the city. It was aimed to develop a framework for a sustainable transportation system for Faisalabad city to cope with severe health impacts. Peak and average values were measured at significant locations, and GIS maps were also drawn spatially to demonstrate clusters of dense traffic at specific time. Furthermore, GS+ and Geostatistical module of Arc GIS 9.3 were used for evaluating sound level data. First, the data were analyzed in GS+, after doing calculation, the best possible model with the highest coefficient of determination (R ) and the minimum error of estimation (RSS) was selected, and the performance of each model was tested using cross-validation and the model which gives best result was used. Spatial prediction maps of noise level data for all the four towns of Faisalabad city were prepared by using the kriging method. Alarmingly high noise levels were observed during peak hours at specific locations. Such findings lead to the development of a framework for a sustainable transportation system to reduce the negative impact on the residents. 1. Introduction population of Faisalabad city, and thus, traffic density is increasing linearly with population density. According to Noise pollution is a machine-generated environmental a previously conducted survey, the hearing capability of threat that disturbs the activities and balance of human the people living in this environment of such a huge life. The noise being produced by the other sources may traffic density is at risk (Ali & Tamura, 2003). become hazardous due to its unacceptable impacts Noise exposure is increasingly being seen as an impor- (Pettersson, 1997). Noise is a phenomenon that has phy- tant environmental public health issue (Clark & siological and psychological effects on human. It is Stansfeld, 2007). Persistent exposure to noise is injurious a significant environmental problem in many urban to health (Boateng & Amedofu, 2004). The damage areas. There are different kinds of noise sources. caused by noise pollution is related to the intensity of Specifically, traffic noise exerts an intense impact on the sound or the amount of energy it has (Bashorun & residents nearby densely populated areas. Noise pollution Olamiju, 2013). is increasing speedily due to immense traffic load on the Environmental noise can cause tinnitus, hearing roads, lack of awareness, unconsciousness of vehicles loss, sleep disturbance, and other harmful effects on impairment, and transportation. High noise levels can health (Mead, 2007). Exposure to noise disturbs sleep conduce to cardiovascular effects in humans and increas- proportional to the amount of noise experienced in ing effects of coronary artery disease. Attention on noise terms of an increased rate of changes in sleep stages pollution has not been paid up to such a level as other and in the number of awakenings (Olokooba et al., environmental problems have gained. Faisalabad is the 2010). Sleep disturbances such as difficulty to fall third most populated city of Pakistan, housing various asleep, alterations of sleep pattern or depth, and awa- types of industries. Population of this city is increasing kenings may necessitate the need for using sleeping progressively. Demands of vehicles for traveling require- pills or ear plugs (Olaosun et al., 2009). ments are also increasing day by day due to the increasing CONTACT Sehrish Latif sehrishlatif21@yahoo.com University of Agriculture, Faisalabad, 38000 Pakistan © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 S. LATIF ET AL. Noise can cause annoyance and aggression degree of interference that noise causes in everyday (Mead, 2007). Studies on traffic and aircraft noise activities precedes or leads to annoyance (Stansford have shown that the noise level has been associated & Matheson, 2003). with annoyance in a close-response relationship The non-auditory effects of noise on humans are and both fear of the noise source and sensitivity viewed as being generally stress-related, following to noise were found to strongly affect the annoy- observations that noise exposures engender physiolo- ance from noise (Miedema & Vos, 1999). The gical reactions typical to those of stress (Ouis, 2001). Figure 1. Study areaE, map of Faisalabad city. Figure 2. Sampling sites of Faisalabad city. GEOLOGY, ECOLOGY, AND LANDSCAPES 3 Noise seems to have a negative effect on performance. 2. Materials and methods It appears that the longer the exposure, the greater the This research was conducted in Faisalabad city, effect. Children from noisy areas have been found to which is situated about 135 kilometers towards have heightened sympathetic arousal indicated by west from provincial capital Lahore with increased levels of stress-related hormones (Goines & a latitude of 31.421045° N, a longitude of Hagler, 2007). High-level noise will result in hearing 73.089294° E, and an altitude of 184 m above the loss (Donatelle, 2002). Evidence abound that constant mean sea level. noise exposure can damage sensitive structures in the ear. Noise-induced hearing loss, the second to age- induced hearing loss, results from damage of the hair 2.1. Site selection cells of the cochlea in the inner ear arising from con- tinuous exposure to recreational and occupational Site selection in the study area is based on the noise (Rabinowitz, 2000). Blasts and other intense or estimation that each selected site should be the explosive sounds can rupture the eardrum or cause illustration of the spatial distribution of noise in immediate damage to the structures of the middle and Faisalabad (Figure 1). Faisalabad is the third largest inner ear, while hearing loss due to prolonged noise city having a population of 3,029,547, of which exposure is generally associated with destruction of almost 42% people live in city. The noise level the hair cells of the inner ear (Olaosun et al., 2009). will be measured at significant sites including Unfamiliarity of vehicle impairment, industrial Main gate of University of Agriculture Faisalabad, development, poor urban planning, conveyance, and (UAF), Jinnah Colony, Clock Tower, Kohinoor construction activities are main factors that cause Plaza, Bus Station, Allied Hospital, GTS Chowk, noise pollution in urban zones. Hearing loss, pressure Jhaal shopping road, GC University, and DHQ of circulating blood, increased hostility headaches, hospital, Nishatabad and Ghulam Muhammad migraine, higher fat levels, irritability insomnia, gas- Abad at selected time intervals (Figure 2). The tric ulcers, and psychological perturb are the impor- experimentation and data collection were con- tant health risks initiated from pollution of noise ducted from February 2018 to June 2018 in differ - (Haines et al., 2005). Another study was conducted ent segments, after dividing the study area in to check the variation in traffic equivalent noise levels different zones as described earlier. The research as the distance from the road connection increases plan has been explained in detail in the succeeding (Abo-Qudais & Alhiary, 2004). Even the people in section. the zone of Katchehry Bazaar (Faisalabad), which is the heart of the town and center of commercial activ- 2.2. Data description ities, were constantly exposed to an average noise level of 93.5 dB for about 10 to 12 hours daily (Hussain The data related to noise pollution were taken et al., 2008). using a Sound Level Meter, and a GPS meter was In Pakistan, due to unawareness about traffic rules, used to find the latitude and longitude of different lack of sophisticated transport facilities, and adverse sampling locations. The data obtained were road conditions, most of the major cities are facing further processed and analyzed by using GIS for severe traffic problems. It leads to road accidents and making maps in Arc GIS 9 (version 9.3) and using increased noise levels. Such adverse situations result in the Kriging technique, a salient feature of Arc GIS. mental stress, fatigue, and anxiety, which may develop a chronic impact on the health of residents who come across this condition for longer durations. This 2.3. Experimental Methodology research work was conducted in Faisalabad, the third highly populated city of Pakistan and a well- Sound levels were measured at three (3) peak established industrial hub. There are severe problems hours (8:00–9:00 am, 1:00–2:00 pm, and 7:00– faced on a daily basis regarding poor transportation 8:00 pm) in a day. Sound levels were noted at systems and intensely high noise levels on roads. It is every five (5)-minute interval during every resulting in an ill impact on the health of the residents, peak hour. This measurement was performed which are suffering from the diseases that are asso- with the sound level meter keeping at arm’s ciated with mental stress and heart-related issues. This length. The sound meter had also been calibrated research was aimed to work out spatial distribution of before taking readings at every site. The peak and different noise level generation zones under different average values were taken for GIS mapping. conditions of time and traffic load; furthermore, it was A health survey questionnaire was developed so also planned to develop a framework for traffic man- agement to reduce the impact of pollution on the that the impact of noise on human health could be residents of Faisalabad city. concluded. 4 S. LATIF ET AL. variogram models. Similarly, Table 3 is about statisti- 2.4. Geostatistical approach cal data analysis of peak noise levels at the same 12 After collection of data, normalization of data was sampling sites and Table 4 explains the cross valida- done. Kriging was found to be the best available tech- tion of characteristic parameters using variogram nique for interpolation and normal distribution of model data. The Kriging method was used in this study for spatial variation analysis. 3.1.1. Average noise level data (8:00-9:00 am) Figure 3 shows the histogram transformation techni- 2.4.1. Exploratory data analysis que applied to normalize data. During normalization Exploratory data analysis was executed to check and of data, skewness, kurtosis, and standard deviation explore data uniformity and consistency and (SD) are calculated. All the values of these parameters remove outliers, identifying statistical distribution. showed that the sound level data are normalized. The The normal Quantile-Quantile plot (Q-Q plots) and histogram shows that the maximum average value of histogram were plotted to check the normality of the sound level peak hour 8–9 am for selected sites is observed data. Histogram and Q-Q Plot analyses were 99.82 dB and the minimum value is 87.00 dB. Figure executed for the water table depth and each water 4 demonstrates Normal Q-Q plot of average Noise quality parameter, and it was found that all the ana- level data. lyzed parameters showed mostly a normal distribution For these sound level data, variograms are drawn. by calculating the median, mean standard deviation Figure 5 shows that the Gaussian model is the best fit (SD), skewness, and kurtosis for each sample. model for these sound level data and demonstrates the spatial variation of data. GIS mapping was performed to show the variation 3. Results and discussion in the sound level data for all selected sites in 3.1. Traffic noise level studies at critical sampling Faisalabad city. Due to this, it is easy to assess the locations in the study area data variation for different timings and locations. The GIS map in Figure 6 demonstrates that the max- Table 1 shows the statistical data analysis of average noise levels at 12 sampling sites., while Table 2 is about imum value was at Bus Station, while Clock Tower the cross validation of characteristic parameters using demonstrates lesser sound levels during this peak Figure 3. Histogram of average noise level data. Figure 4. Normal Q-Q plot of average noise level data. GEOLOGY, ECOLOGY, AND LANDSCAPES 5 Figure 5. Gaussian model for average noise level data (8.00–9.00 AM). Figure 6. GIS map of average sound level data (8–9 am). Figure 7. Histogram of average noise level data. timing. It was because at the clock tower, most of 3.1.2. Average sound level data (1:00-2:00 pm) the business activity started after 9:00 am, while Data were normalized by drawing histograms of sound levels bus stops were crowded due to office and school during the peak hour. In Figure 7, the values of the parameters have shown that there existed consistency in data. timings. 6 S. LATIF ET AL. Figure 8. Normal Q-Q plot of average noise level data. GIS mapping was performed to show the variation in the sound level data for all selected sites in Faisalabad city. Due to this, it is easy to assess the data. The map shows that the maximum value was at Bus Station, while GC University has a less sound level during this timing. The GIS map of sound level variation at different sam- pling points during this time interval is shown in Figure 14. Maximum levels of sound could be observed at the Koh e noor commercial area due to peak hours of commercial activity. Similarly, high values have also been observed in the Allied hospital area. Figure 9. Gaussian model for average noise level data (1.00– 2.00 PM). 3.1.4. Peak sound level data (8:00-9:00 pm) Data were normalized by drawing histograms of By checking uniformity of data, variograms were sound levels during the peak hour. In Figure 15, the drawn as shown in Figure 8, while Figure 9 shows that values of the parameters showed that data have been the Gaussian model is the model that fulfilled the consistent. conditions of the statistical variations. The mean By checking the uniformity of data, variograms error, root mean square error, ASE, MSE, and RMSE were drawn (Figure 16). Figure 17 shows that the were calculated for this model. Gaussian model is the model that fulfills the condi- During this time interval from 1:00 pm to 2:00 PM, tions of the statistical variations. The mean error, root from Figure 10, it has been observed that the mean square error, ASE, MSE, and RMSE were calcu- peak hour maximum sound level was 99.82 dB at lated for this model. Allied Hospital and the minimum was 87.01 dB at The GIS map for peak values for all the sampling the Clock Tower. locations has shown that the maximum sound level was 113.9 dB at DHQ Hospital and the minimum was 88.90 dB at Clock Tower (Figure 18). 3.1.3. Average sound level data (7:00-8:00 pm) Figure 11 demonstrates that the histogram transfor- mation technique is applied to normalize data. During 3.1.5. Peak sound level data (1:00-2:00 am) normalization of data, skewness, kurtosis, and stan- Figure 19 shows that the histogram transformation dard deviation (SD) are calculated. All the values of technique is applied to normalize data. During nor- these parameters show that the sound level data are malization of data, skewness, kurtosis, and standard normalized. The histogram (Figure 11) also shows that deviation (SD) have been calculated. All the values of the maximum average value of sound level peak hour these parameters showed that the sound level data are 7–8 pm for selected sites is 101.6 dB and the minimum normalized. The histogram showed that the maximum value is 85.03 dB. average value of sound level at peak hour 1–2 am for By checking uniformity of data, variograms were selected sites is 109.4 dB and the minimum value is drawn as shown in Figure 12, while Figure 13 95.2 dB. shows that the spherical model is the model that fulfills For this sound level, data variograms are drawn as the conditions of the statistical variations. The mean shown in Figure 20, while Figure 21 shows that the error, root mean square error, ASE, MSE, and RMSE Gaussian model is the best fit model for these sound were calculated for this model. level data and exhibited spatial variation of data. GEOLOGY, ECOLOGY, AND LANDSCAPES 7 Figure 10. GIS map of average sound level data (1–2 pm). Figure 11. Histogram of average noise level data. Figure 12. Normal Q-Q plot of average noise level data. 8 S. LATIF ET AL. Table 1. Statistical analysis of average noise levels at 12 sites. GIS mapping (Figure 22) was performed to L L L show the variation in the sound level data for all avg avg avg Timing (min) (max) (mean) SD Kurtosis Skewness selected sites in Faisalabad city. Due to this, it is 8:00–9:00 87 97.8 94.2 3.01 2.68 0.018 easy to assess the data. The map showed that the am 1:00–2:00 87.0 99.8 93.4 3.016 2.68 0.018 maximum value was at Allied Hospital, while pm Clock Tower has a less sound level during this 7:00–8:00 88.3 101.6 94.7 3.300 3.40 0.149 pm timing. Table 2. Cross-validation of L (characteristic parameters of variogram models). avg Average Average sound level Mean Root Mean Square Standard Mean Standardized Root Mean Square Standardized Best fit L Error Error Error Error Error model avg 8:00–9:00 am 0.8812 6.513 7.496 0.09495 0.8612 Gaussian 1:00–2:00 pm 0.2664 4.216 4.724 0.04386 0.8914 Gaussian 7:00–8:00 pm 0.244 3.943 4.088 0.05568 0.9722 Spherical Figure 13. Spherical model for average noise level data (7.00–8.00 AM). Figure 14. GIS map of average sound level data (7–8 pm). GEOLOGY, ECOLOGY, AND LANDSCAPES 9 3.1.6. Peak sound level data (7:00-8:00 pm) statistical variations. The mean error, root mean Data were normalized by drawing histograms of sound square error, ASE, MSE, and RMSE were calculated levels during the peak hour. In Figure 23, the values of for this model. the parameters showed that data have consistency. It is obvious from GIS mapping shown in By checking uniformity of data, variograms were Figure 26 that during this peak hour, the maximum drawn (Figure 24). Figure 25 shows that the Spherical sound level was 108.8 dB at Bus Station and the model is the model that fulfills the conditions of the minimum was 91.7 dB at GC University. These Figure 15. Histogram of peak noise level data. Figure 16. Normal Q-Q plot of peak noise level data. Figure 17. Gaussian model for peak noise level data (8.00–9.00 AM). 10 S. LATIF ET AL. Figure 18. GIS map of peak sound level data (8–9 am). Figure 19. Histogram of peak noise level data. Figure 20. Normal Q-Q plot of peak noise level data. GEOLOGY, ECOLOGY, AND LANDSCAPES 11 Figure 21. Gaussian model for peak noise level data (1.00–2.00 PM). Figure 22. GIS map of peak sound level data (1–2 pm). Figure 23. Histogram of peak noise level data. 12 S. LATIF ET AL. Figure 24. Normal Q-Q plot of peak noise level data. results clearly depicted the existing situation at the Traffic volume reduction through a sustainable sampling locations and the sound level variations approach for different time zones. Reduction of the negative impact on the environ- ment and human health 4. Sustainable transport management Based on the findings of the research work conducted framework in the study area and major observations identified, the framework for sustainable transport management Ultimate goals and policy guideline of the Sustainable was developed, considering the predefined policy and Transport Management Framework for Faisalabad goals. Salient features of this framework have been city, having a population of about 3.0 Million at the explained in successive paragraphs, which once imple- time of study, were defined as follows; mented, can have a significant impact on the environ- ment, human health, and quality of living of the city. Table 3. Statistical analysis of peak noise levels at 12 sampling sites. 4.1. Traffic control and road safety and L L L peak peak peak maintenance Timing (min) (max) (mean) SD Kurtosis Skewness 8:00–9:00 88.9 113.9 98.4 5.452 3.07 0.826 Traffic signals and strict observation of traffic rules are am the most powerful devices for traffic control. Traffic 1:00–2:00 95.1 108.9 102.9 3.637 3.23 −0.709 signals must be installed at every important crossing, pm 7:00–8:00 91.7 108.8 104.1 2.699 3.14 −0.439 and it should be followed strictly. Using latest artificial pm Table 4. Cross-validation of L (characteristic parameters of variogram models). peak Average sound level Mean Root Mean Square Average Standard Mean Standardized Root Mean Square Standardized Best Fit L Error Error Error Error Error Model peak 8:00–9:00am 1.723 8.58 11.06 0.1288 0.825 Gaussian 1:00–2:00 pm 0.2894 5.108 5.947 0.03317 0.8669 Gaussian 7:00–8:00 pm −0.0483 5.401 5.863 −0.008287 0.9221 Spherical Figure 25. Spherical model for peak noise level data (7.00–8.00 PM). GEOLOGY, ECOLOGY, AND LANDSCAPES 13 Figure 26. GIS map of peak sound level data (7–8 pm). intelligence, the duration of traffic signals for peak help in reducing the negative psychological impacts on hours should be optimized to maintain the consis- the drivers and will facilitate safe journey. Low-power tency in the traffic flow and avoid the undue delay in motor bikes should be encouraged within city, and shifting the traffic at the signals. Considering the on- there should be separate lane marked and reserved field traffic control requirements, lane rules should be only for light weight motor bikes and cycles and strictly implemented, particularly during rush hours. other such vehicles. Fixation of road studs near crossings and diversions would facilitate its implementation. Traffic rules 4.2. Adaptation of economical traffic routing for awareness among the drivers of all categories of vehi- Faisalabad city by urban planning cles must be ensured, and there should be identifica - tion of traffic signs, which must be displayed at Instead of clustering of infrastructure and facilities, significant places. Initially, for the purpose of aware- uniform distribution and dispersal of resources ness of drivers, unaware of traffic rules, help and should be planned. It can also be expressed as decen- assistance from well-trained college students could tralization of urban resources. It would lead to paral- be acquired. Media campaigns should be initiated to lel growth of the city in all directions, resulting in the influence public about the road safety and traffic noise reduction of need to travel across the urban locality to pollution. Penalty should be enforced to those who reach other corners of the city to access a particular break the traffic rules, and by adopting digital and commodity/facility. For a sustainable transport sys- automatic means for controlling the traffic, strict sur- tem, it is important to develop cities in such a manner veillance could be ensured. Modes of transport should to facilitate non-motorized transport management for be limited during specific hours, allowing only certain the city. Only reliance on public transport will not vehicles to move through crowded vicinities and suffice the need, but it is also required that the urban important areas, like hospitals and schools, for exam- planning should be done to optimize the travelling ple, animal driven carts, trucks, and intercity buses. demands of the residents in terms of land allocation Improvement of quality of roads to facilitate to specific purpose including hospitals, schools, mar- smooth flow of traffic causes lesser noise and lesser kets, and residential areas. It must be planned to risk of accidents. There should be a standard green belt reduce the load on major hospitals of the city, i.e., separating the two-way traffic. This green belt must Allied Hospital on the western side. Instead of work as a buffer zone to reduce the impact of noise extending the scope of this hospital, it is proposed and at the same time, reduce the intensity of high to plan a state-of-the-art hospital with advanced treat- beam lights of traffic coming from other sides. It will ment facilities on the eastern side of the city as well. 14 S. LATIF ET AL. Similarly, high schools and other teaching institutions establish urban mass transit facility along all these should be properly located to equally distribute the roads, having interconnecting points at significant load at peak hours of transportation. Proper urban places. planning for economical traffic routing is more feasi- ble for newly developed urban communities. But for older cities like Faisalabad, the best possible approach 4.4. Traffic sorting/uniformity in the vehicle size could be “Radial Wheel Concept.” It is about con- and category necting all important locations through “ring roads,” A well-sorted transportation system would facilitate in with inner and outer circles. A Ring Road project is ease with which the traffic will flow smoothly in the need of the hour for Faisalabad city to interlink a particular direction. But if there are a variety of vehicles the alarmingly extending boundaries of the city. of all sizes and categories, it would hinder the continuity Particularly, due to the development of Industrial in the traffic flow. Keeping in view the typical scenario of Zones on M-3 motorway, it is required to plan traffic accustomed in Faisalabad city, intrusion of all a ring road across the city to reduce the overcrowded kinds of traffic vehicles caused traffic problems, particu- mid-town traffic. larly during peak rush hours. Therefore, it is important to limit the vehicle size and category to run on the roads, while other vehicles should be provided alternate service 4.3. Urban mass transit (UMT) for Faisalabad city roads. If service roads are not possible to be developed, Government must develop such policies to encou- there should be clear separation through road studs and rage public transport mode rather than individual partitioning on the main roads to distinguish different transport. A mega urban mass transit project would kinds of vehicles. Three-wheel drives and animal-driven be the most appropriate solution to reduce the carts must be replaced with a more stable vehicle for traffic load on the roads. Frequency of urban mass luggage carriage. The mode of transports must be limited transit can be optimized based on the mass transit during specific hours, and only certain vehicles should be influx requirements, which may vary time to time allowed to move through crowded vicinities and impor- throughout the day. Having an urban mass transit tant areas, like hospitals and schools. The vehicles to be would reduce the traffic density on the main roads excluded from the main roads during peak hours include by reducing the demand of traffic vehicles, particu- animal carts, three wheelers, intercity bus services, and larly the private ones. The presence of more private load carrying trucks. vehicles on the roads results in unwanted space A concise framework for a sustainable traffic manage- occupancy with lesser productivity. Due to wide ment system, ideally to be implemented in Faisalabad expansion of Faisalabad city along Satiana Road, city, in particular, and, generally, for any other place Jhang Road, Sargodha Road, Lahore Road, and with similar characteristics and traffic behaviour and Samandari Road, it is highly recommended to issues is represented in Figure 27. Subjected to Figure 27. Four roads to a sustainable transportation system in Faisalabad city. GEOLOGY, ECOLOGY, AND LANDSCAPES 15 establishment, this framework in Faisalabad city would Bashorun, J. O., & Olamiju, I. O. (2013). Environmental pollution and refinery operations in an oil producing lead to a sustainable transport management system in the region of Nigeria: A focus on warri petrochemical city and will reduce the air and noise pollution issues company. 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International Journal of Comparative hospital, Allied hospital, Main gate of UAF, Bus Psychology, 20(2), 145–158. https://escholarship.org/uc/ station, and GTS chowk during peak hours. item/8434889m During 8–9 am, the noise level at the main gate Donatelle, R. J. (2002). Access to health (7th ed.). Benjamin of UAF was maximum because timing of university Cummings Publishers. starts from 8 am and there was a huge rush of Goines, L., & Hagler, L. (2007). Noise pollution: A modern plague. Southern Medical Journal, 100(3), 287–293. bikes, cars and rickshaws. The maximum value of https://doi.org/10.1097/SMJ.0b013e3180318be5 noise was 113 dB at DHQ hospital during 8–9 am. Haines, M. M., Bretnall., S. L., Stansfeld, S. A., & This means that there is huge rush of traffic at that Klineberg, E. (2005). Qualitative responses of children time. During 8–9 am, at most of the other sites, the to environmental noise. 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British Medical Bulletin, Applied Acoustics, 64(8), 815–823. https://doi.org/10. 68(1), 243–257. https://doi.org/10.1093/bmb/ldg033 1016/S0003-682X(03)00031-8 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Geology Ecology and Landscapes Taylor & Francis

Impact Assessment of Traffic Noise in a Densely Populated Industrial City, Faisalabad Pakistan Using Geostatistical Approach and Development of Sustainable Transportation System Framework

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GEOLOGY, ECOLOGY, AND LANDSCAPES INWASCON https://doi.org/10.1080/24749508.2021.2022575 RESEARCH ARTICLE Impact Assessment of Traffic Noise in a Densely Populated Industrial City, Faisalabad Pakistan Using Geostatistical Approach and Development of Sustainable Transportation System Framework Sehrish Latif, Haroon Rashid and Abdul Nasir Department of Structures & Environmental Engineering, University of Agriculture, Faisalabad, Pakistan ABSTRACT ARTICLE HISTORY Received 1 March 2021 Haphazard and noisy traffic in congested and densely populated old cities has become Accepted 7 October 2021 a challenge for the environmental and transportation engineers to provide better means of transportation with raised quality of life and environment. Faisalabad is an old and major KEYWORDS industrial city of Pakistan, which has huge influx of population due to its industrial significance. Sustainable transportation It has been facing severe traffic issues, which result in a noisy and irritating environment all system; noise pollution; around. This research work was planned to find out the health impact of noisy traffic on the haphazard traffic; heavy residents and their social life, determining noise level variation trends with the changing traffic; geostatistical analysis; health impact density of traffic at different time intervals in a day and how variations occur during different weekdays. This study was focused to enquire the severity of noise levels due to road traffic with reference to significant selected locations throughout the city. It was aimed to develop a framework for a sustainable transportation system for Faisalabad city to cope with severe health impacts. Peak and average values were measured at significant locations, and GIS maps were also drawn spatially to demonstrate clusters of dense traffic at specific time. Furthermore, GS+ and Geostatistical module of Arc GIS 9.3 were used for evaluating sound level data. First, the data were analyzed in GS+, after doing calculation, the best possible model with the highest coefficient of determination (R ) and the minimum error of estimation (RSS) was selected, and the performance of each model was tested using cross-validation and the model which gives best result was used. Spatial prediction maps of noise level data for all the four towns of Faisalabad city were prepared by using the kriging method. Alarmingly high noise levels were observed during peak hours at specific locations. Such findings lead to the development of a framework for a sustainable transportation system to reduce the negative impact on the residents. 1. Introduction population of Faisalabad city, and thus, traffic density is increasing linearly with population density. According to Noise pollution is a machine-generated environmental a previously conducted survey, the hearing capability of threat that disturbs the activities and balance of human the people living in this environment of such a huge life. The noise being produced by the other sources may traffic density is at risk (Ali & Tamura, 2003). become hazardous due to its unacceptable impacts Noise exposure is increasingly being seen as an impor- (Pettersson, 1997). Noise is a phenomenon that has phy- tant environmental public health issue (Clark & siological and psychological effects on human. It is Stansfeld, 2007). Persistent exposure to noise is injurious a significant environmental problem in many urban to health (Boateng & Amedofu, 2004). The damage areas. There are different kinds of noise sources. caused by noise pollution is related to the intensity of Specifically, traffic noise exerts an intense impact on the sound or the amount of energy it has (Bashorun & residents nearby densely populated areas. Noise pollution Olamiju, 2013). is increasing speedily due to immense traffic load on the Environmental noise can cause tinnitus, hearing roads, lack of awareness, unconsciousness of vehicles loss, sleep disturbance, and other harmful effects on impairment, and transportation. High noise levels can health (Mead, 2007). Exposure to noise disturbs sleep conduce to cardiovascular effects in humans and increas- proportional to the amount of noise experienced in ing effects of coronary artery disease. Attention on noise terms of an increased rate of changes in sleep stages pollution has not been paid up to such a level as other and in the number of awakenings (Olokooba et al., environmental problems have gained. Faisalabad is the 2010). Sleep disturbances such as difficulty to fall third most populated city of Pakistan, housing various asleep, alterations of sleep pattern or depth, and awa- types of industries. Population of this city is increasing kenings may necessitate the need for using sleeping progressively. Demands of vehicles for traveling require- pills or ear plugs (Olaosun et al., 2009). ments are also increasing day by day due to the increasing CONTACT Sehrish Latif sehrishlatif21@yahoo.com University of Agriculture, Faisalabad, 38000 Pakistan © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2 S. LATIF ET AL. Noise can cause annoyance and aggression degree of interference that noise causes in everyday (Mead, 2007). Studies on traffic and aircraft noise activities precedes or leads to annoyance (Stansford have shown that the noise level has been associated & Matheson, 2003). with annoyance in a close-response relationship The non-auditory effects of noise on humans are and both fear of the noise source and sensitivity viewed as being generally stress-related, following to noise were found to strongly affect the annoy- observations that noise exposures engender physiolo- ance from noise (Miedema & Vos, 1999). The gical reactions typical to those of stress (Ouis, 2001). Figure 1. Study areaE, map of Faisalabad city. Figure 2. Sampling sites of Faisalabad city. GEOLOGY, ECOLOGY, AND LANDSCAPES 3 Noise seems to have a negative effect on performance. 2. Materials and methods It appears that the longer the exposure, the greater the This research was conducted in Faisalabad city, effect. Children from noisy areas have been found to which is situated about 135 kilometers towards have heightened sympathetic arousal indicated by west from provincial capital Lahore with increased levels of stress-related hormones (Goines & a latitude of 31.421045° N, a longitude of Hagler, 2007). High-level noise will result in hearing 73.089294° E, and an altitude of 184 m above the loss (Donatelle, 2002). Evidence abound that constant mean sea level. noise exposure can damage sensitive structures in the ear. Noise-induced hearing loss, the second to age- induced hearing loss, results from damage of the hair 2.1. Site selection cells of the cochlea in the inner ear arising from con- tinuous exposure to recreational and occupational Site selection in the study area is based on the noise (Rabinowitz, 2000). Blasts and other intense or estimation that each selected site should be the explosive sounds can rupture the eardrum or cause illustration of the spatial distribution of noise in immediate damage to the structures of the middle and Faisalabad (Figure 1). Faisalabad is the third largest inner ear, while hearing loss due to prolonged noise city having a population of 3,029,547, of which exposure is generally associated with destruction of almost 42% people live in city. The noise level the hair cells of the inner ear (Olaosun et al., 2009). will be measured at significant sites including Unfamiliarity of vehicle impairment, industrial Main gate of University of Agriculture Faisalabad, development, poor urban planning, conveyance, and (UAF), Jinnah Colony, Clock Tower, Kohinoor construction activities are main factors that cause Plaza, Bus Station, Allied Hospital, GTS Chowk, noise pollution in urban zones. Hearing loss, pressure Jhaal shopping road, GC University, and DHQ of circulating blood, increased hostility headaches, hospital, Nishatabad and Ghulam Muhammad migraine, higher fat levels, irritability insomnia, gas- Abad at selected time intervals (Figure 2). The tric ulcers, and psychological perturb are the impor- experimentation and data collection were con- tant health risks initiated from pollution of noise ducted from February 2018 to June 2018 in differ - (Haines et al., 2005). Another study was conducted ent segments, after dividing the study area in to check the variation in traffic equivalent noise levels different zones as described earlier. The research as the distance from the road connection increases plan has been explained in detail in the succeeding (Abo-Qudais & Alhiary, 2004). Even the people in section. the zone of Katchehry Bazaar (Faisalabad), which is the heart of the town and center of commercial activ- 2.2. Data description ities, were constantly exposed to an average noise level of 93.5 dB for about 10 to 12 hours daily (Hussain The data related to noise pollution were taken et al., 2008). using a Sound Level Meter, and a GPS meter was In Pakistan, due to unawareness about traffic rules, used to find the latitude and longitude of different lack of sophisticated transport facilities, and adverse sampling locations. The data obtained were road conditions, most of the major cities are facing further processed and analyzed by using GIS for severe traffic problems. It leads to road accidents and making maps in Arc GIS 9 (version 9.3) and using increased noise levels. Such adverse situations result in the Kriging technique, a salient feature of Arc GIS. mental stress, fatigue, and anxiety, which may develop a chronic impact on the health of residents who come across this condition for longer durations. This 2.3. Experimental Methodology research work was conducted in Faisalabad, the third highly populated city of Pakistan and a well- Sound levels were measured at three (3) peak established industrial hub. There are severe problems hours (8:00–9:00 am, 1:00–2:00 pm, and 7:00– faced on a daily basis regarding poor transportation 8:00 pm) in a day. Sound levels were noted at systems and intensely high noise levels on roads. It is every five (5)-minute interval during every resulting in an ill impact on the health of the residents, peak hour. This measurement was performed which are suffering from the diseases that are asso- with the sound level meter keeping at arm’s ciated with mental stress and heart-related issues. This length. The sound meter had also been calibrated research was aimed to work out spatial distribution of before taking readings at every site. The peak and different noise level generation zones under different average values were taken for GIS mapping. conditions of time and traffic load; furthermore, it was A health survey questionnaire was developed so also planned to develop a framework for traffic man- agement to reduce the impact of pollution on the that the impact of noise on human health could be residents of Faisalabad city. concluded. 4 S. LATIF ET AL. variogram models. Similarly, Table 3 is about statisti- 2.4. Geostatistical approach cal data analysis of peak noise levels at the same 12 After collection of data, normalization of data was sampling sites and Table 4 explains the cross valida- done. Kriging was found to be the best available tech- tion of characteristic parameters using variogram nique for interpolation and normal distribution of model data. The Kriging method was used in this study for spatial variation analysis. 3.1.1. Average noise level data (8:00-9:00 am) Figure 3 shows the histogram transformation techni- 2.4.1. Exploratory data analysis que applied to normalize data. During normalization Exploratory data analysis was executed to check and of data, skewness, kurtosis, and standard deviation explore data uniformity and consistency and (SD) are calculated. All the values of these parameters remove outliers, identifying statistical distribution. showed that the sound level data are normalized. The The normal Quantile-Quantile plot (Q-Q plots) and histogram shows that the maximum average value of histogram were plotted to check the normality of the sound level peak hour 8–9 am for selected sites is observed data. Histogram and Q-Q Plot analyses were 99.82 dB and the minimum value is 87.00 dB. Figure executed for the water table depth and each water 4 demonstrates Normal Q-Q plot of average Noise quality parameter, and it was found that all the ana- level data. lyzed parameters showed mostly a normal distribution For these sound level data, variograms are drawn. by calculating the median, mean standard deviation Figure 5 shows that the Gaussian model is the best fit (SD), skewness, and kurtosis for each sample. model for these sound level data and demonstrates the spatial variation of data. GIS mapping was performed to show the variation 3. Results and discussion in the sound level data for all selected sites in 3.1. Traffic noise level studies at critical sampling Faisalabad city. Due to this, it is easy to assess the locations in the study area data variation for different timings and locations. The GIS map in Figure 6 demonstrates that the max- Table 1 shows the statistical data analysis of average noise levels at 12 sampling sites., while Table 2 is about imum value was at Bus Station, while Clock Tower the cross validation of characteristic parameters using demonstrates lesser sound levels during this peak Figure 3. Histogram of average noise level data. Figure 4. Normal Q-Q plot of average noise level data. GEOLOGY, ECOLOGY, AND LANDSCAPES 5 Figure 5. Gaussian model for average noise level data (8.00–9.00 AM). Figure 6. GIS map of average sound level data (8–9 am). Figure 7. Histogram of average noise level data. timing. It was because at the clock tower, most of 3.1.2. Average sound level data (1:00-2:00 pm) the business activity started after 9:00 am, while Data were normalized by drawing histograms of sound levels bus stops were crowded due to office and school during the peak hour. In Figure 7, the values of the parameters have shown that there existed consistency in data. timings. 6 S. LATIF ET AL. Figure 8. Normal Q-Q plot of average noise level data. GIS mapping was performed to show the variation in the sound level data for all selected sites in Faisalabad city. Due to this, it is easy to assess the data. The map shows that the maximum value was at Bus Station, while GC University has a less sound level during this timing. The GIS map of sound level variation at different sam- pling points during this time interval is shown in Figure 14. Maximum levels of sound could be observed at the Koh e noor commercial area due to peak hours of commercial activity. Similarly, high values have also been observed in the Allied hospital area. Figure 9. Gaussian model for average noise level data (1.00– 2.00 PM). 3.1.4. Peak sound level data (8:00-9:00 pm) Data were normalized by drawing histograms of By checking uniformity of data, variograms were sound levels during the peak hour. In Figure 15, the drawn as shown in Figure 8, while Figure 9 shows that values of the parameters showed that data have been the Gaussian model is the model that fulfilled the consistent. conditions of the statistical variations. The mean By checking the uniformity of data, variograms error, root mean square error, ASE, MSE, and RMSE were drawn (Figure 16). Figure 17 shows that the were calculated for this model. Gaussian model is the model that fulfills the condi- During this time interval from 1:00 pm to 2:00 PM, tions of the statistical variations. The mean error, root from Figure 10, it has been observed that the mean square error, ASE, MSE, and RMSE were calcu- peak hour maximum sound level was 99.82 dB at lated for this model. Allied Hospital and the minimum was 87.01 dB at The GIS map for peak values for all the sampling the Clock Tower. locations has shown that the maximum sound level was 113.9 dB at DHQ Hospital and the minimum was 88.90 dB at Clock Tower (Figure 18). 3.1.3. Average sound level data (7:00-8:00 pm) Figure 11 demonstrates that the histogram transfor- mation technique is applied to normalize data. During 3.1.5. Peak sound level data (1:00-2:00 am) normalization of data, skewness, kurtosis, and stan- Figure 19 shows that the histogram transformation dard deviation (SD) are calculated. All the values of technique is applied to normalize data. During nor- these parameters show that the sound level data are malization of data, skewness, kurtosis, and standard normalized. The histogram (Figure 11) also shows that deviation (SD) have been calculated. All the values of the maximum average value of sound level peak hour these parameters showed that the sound level data are 7–8 pm for selected sites is 101.6 dB and the minimum normalized. The histogram showed that the maximum value is 85.03 dB. average value of sound level at peak hour 1–2 am for By checking uniformity of data, variograms were selected sites is 109.4 dB and the minimum value is drawn as shown in Figure 12, while Figure 13 95.2 dB. shows that the spherical model is the model that fulfills For this sound level, data variograms are drawn as the conditions of the statistical variations. The mean shown in Figure 20, while Figure 21 shows that the error, root mean square error, ASE, MSE, and RMSE Gaussian model is the best fit model for these sound were calculated for this model. level data and exhibited spatial variation of data. GEOLOGY, ECOLOGY, AND LANDSCAPES 7 Figure 10. GIS map of average sound level data (1–2 pm). Figure 11. Histogram of average noise level data. Figure 12. Normal Q-Q plot of average noise level data. 8 S. LATIF ET AL. Table 1. Statistical analysis of average noise levels at 12 sites. GIS mapping (Figure 22) was performed to L L L show the variation in the sound level data for all avg avg avg Timing (min) (max) (mean) SD Kurtosis Skewness selected sites in Faisalabad city. Due to this, it is 8:00–9:00 87 97.8 94.2 3.01 2.68 0.018 easy to assess the data. The map showed that the am 1:00–2:00 87.0 99.8 93.4 3.016 2.68 0.018 maximum value was at Allied Hospital, while pm Clock Tower has a less sound level during this 7:00–8:00 88.3 101.6 94.7 3.300 3.40 0.149 pm timing. Table 2. Cross-validation of L (characteristic parameters of variogram models). avg Average Average sound level Mean Root Mean Square Standard Mean Standardized Root Mean Square Standardized Best fit L Error Error Error Error Error model avg 8:00–9:00 am 0.8812 6.513 7.496 0.09495 0.8612 Gaussian 1:00–2:00 pm 0.2664 4.216 4.724 0.04386 0.8914 Gaussian 7:00–8:00 pm 0.244 3.943 4.088 0.05568 0.9722 Spherical Figure 13. Spherical model for average noise level data (7.00–8.00 AM). Figure 14. GIS map of average sound level data (7–8 pm). GEOLOGY, ECOLOGY, AND LANDSCAPES 9 3.1.6. Peak sound level data (7:00-8:00 pm) statistical variations. The mean error, root mean Data were normalized by drawing histograms of sound square error, ASE, MSE, and RMSE were calculated levels during the peak hour. In Figure 23, the values of for this model. the parameters showed that data have consistency. It is obvious from GIS mapping shown in By checking uniformity of data, variograms were Figure 26 that during this peak hour, the maximum drawn (Figure 24). Figure 25 shows that the Spherical sound level was 108.8 dB at Bus Station and the model is the model that fulfills the conditions of the minimum was 91.7 dB at GC University. These Figure 15. Histogram of peak noise level data. Figure 16. Normal Q-Q plot of peak noise level data. Figure 17. Gaussian model for peak noise level data (8.00–9.00 AM). 10 S. LATIF ET AL. Figure 18. GIS map of peak sound level data (8–9 am). Figure 19. Histogram of peak noise level data. Figure 20. Normal Q-Q plot of peak noise level data. GEOLOGY, ECOLOGY, AND LANDSCAPES 11 Figure 21. Gaussian model for peak noise level data (1.00–2.00 PM). Figure 22. GIS map of peak sound level data (1–2 pm). Figure 23. Histogram of peak noise level data. 12 S. LATIF ET AL. Figure 24. Normal Q-Q plot of peak noise level data. results clearly depicted the existing situation at the Traffic volume reduction through a sustainable sampling locations and the sound level variations approach for different time zones. Reduction of the negative impact on the environ- ment and human health 4. Sustainable transport management Based on the findings of the research work conducted framework in the study area and major observations identified, the framework for sustainable transport management Ultimate goals and policy guideline of the Sustainable was developed, considering the predefined policy and Transport Management Framework for Faisalabad goals. Salient features of this framework have been city, having a population of about 3.0 Million at the explained in successive paragraphs, which once imple- time of study, were defined as follows; mented, can have a significant impact on the environ- ment, human health, and quality of living of the city. Table 3. Statistical analysis of peak noise levels at 12 sampling sites. 4.1. Traffic control and road safety and L L L peak peak peak maintenance Timing (min) (max) (mean) SD Kurtosis Skewness 8:00–9:00 88.9 113.9 98.4 5.452 3.07 0.826 Traffic signals and strict observation of traffic rules are am the most powerful devices for traffic control. Traffic 1:00–2:00 95.1 108.9 102.9 3.637 3.23 −0.709 signals must be installed at every important crossing, pm 7:00–8:00 91.7 108.8 104.1 2.699 3.14 −0.439 and it should be followed strictly. Using latest artificial pm Table 4. Cross-validation of L (characteristic parameters of variogram models). peak Average sound level Mean Root Mean Square Average Standard Mean Standardized Root Mean Square Standardized Best Fit L Error Error Error Error Error Model peak 8:00–9:00am 1.723 8.58 11.06 0.1288 0.825 Gaussian 1:00–2:00 pm 0.2894 5.108 5.947 0.03317 0.8669 Gaussian 7:00–8:00 pm −0.0483 5.401 5.863 −0.008287 0.9221 Spherical Figure 25. Spherical model for peak noise level data (7.00–8.00 PM). GEOLOGY, ECOLOGY, AND LANDSCAPES 13 Figure 26. GIS map of peak sound level data (7–8 pm). intelligence, the duration of traffic signals for peak help in reducing the negative psychological impacts on hours should be optimized to maintain the consis- the drivers and will facilitate safe journey. Low-power tency in the traffic flow and avoid the undue delay in motor bikes should be encouraged within city, and shifting the traffic at the signals. Considering the on- there should be separate lane marked and reserved field traffic control requirements, lane rules should be only for light weight motor bikes and cycles and strictly implemented, particularly during rush hours. other such vehicles. Fixation of road studs near crossings and diversions would facilitate its implementation. Traffic rules 4.2. Adaptation of economical traffic routing for awareness among the drivers of all categories of vehi- Faisalabad city by urban planning cles must be ensured, and there should be identifica - tion of traffic signs, which must be displayed at Instead of clustering of infrastructure and facilities, significant places. Initially, for the purpose of aware- uniform distribution and dispersal of resources ness of drivers, unaware of traffic rules, help and should be planned. It can also be expressed as decen- assistance from well-trained college students could tralization of urban resources. It would lead to paral- be acquired. Media campaigns should be initiated to lel growth of the city in all directions, resulting in the influence public about the road safety and traffic noise reduction of need to travel across the urban locality to pollution. Penalty should be enforced to those who reach other corners of the city to access a particular break the traffic rules, and by adopting digital and commodity/facility. For a sustainable transport sys- automatic means for controlling the traffic, strict sur- tem, it is important to develop cities in such a manner veillance could be ensured. Modes of transport should to facilitate non-motorized transport management for be limited during specific hours, allowing only certain the city. Only reliance on public transport will not vehicles to move through crowded vicinities and suffice the need, but it is also required that the urban important areas, like hospitals and schools, for exam- planning should be done to optimize the travelling ple, animal driven carts, trucks, and intercity buses. demands of the residents in terms of land allocation Improvement of quality of roads to facilitate to specific purpose including hospitals, schools, mar- smooth flow of traffic causes lesser noise and lesser kets, and residential areas. It must be planned to risk of accidents. There should be a standard green belt reduce the load on major hospitals of the city, i.e., separating the two-way traffic. This green belt must Allied Hospital on the western side. Instead of work as a buffer zone to reduce the impact of noise extending the scope of this hospital, it is proposed and at the same time, reduce the intensity of high to plan a state-of-the-art hospital with advanced treat- beam lights of traffic coming from other sides. It will ment facilities on the eastern side of the city as well. 14 S. LATIF ET AL. Similarly, high schools and other teaching institutions establish urban mass transit facility along all these should be properly located to equally distribute the roads, having interconnecting points at significant load at peak hours of transportation. Proper urban places. planning for economical traffic routing is more feasi- ble for newly developed urban communities. But for older cities like Faisalabad, the best possible approach 4.4. Traffic sorting/uniformity in the vehicle size could be “Radial Wheel Concept.” It is about con- and category necting all important locations through “ring roads,” A well-sorted transportation system would facilitate in with inner and outer circles. A Ring Road project is ease with which the traffic will flow smoothly in the need of the hour for Faisalabad city to interlink a particular direction. But if there are a variety of vehicles the alarmingly extending boundaries of the city. of all sizes and categories, it would hinder the continuity Particularly, due to the development of Industrial in the traffic flow. Keeping in view the typical scenario of Zones on M-3 motorway, it is required to plan traffic accustomed in Faisalabad city, intrusion of all a ring road across the city to reduce the overcrowded kinds of traffic vehicles caused traffic problems, particu- mid-town traffic. larly during peak rush hours. Therefore, it is important to limit the vehicle size and category to run on the roads, while other vehicles should be provided alternate service 4.3. Urban mass transit (UMT) for Faisalabad city roads. If service roads are not possible to be developed, Government must develop such policies to encou- there should be clear separation through road studs and rage public transport mode rather than individual partitioning on the main roads to distinguish different transport. A mega urban mass transit project would kinds of vehicles. Three-wheel drives and animal-driven be the most appropriate solution to reduce the carts must be replaced with a more stable vehicle for traffic load on the roads. Frequency of urban mass luggage carriage. The mode of transports must be limited transit can be optimized based on the mass transit during specific hours, and only certain vehicles should be influx requirements, which may vary time to time allowed to move through crowded vicinities and impor- throughout the day. Having an urban mass transit tant areas, like hospitals and schools. The vehicles to be would reduce the traffic density on the main roads excluded from the main roads during peak hours include by reducing the demand of traffic vehicles, particu- animal carts, three wheelers, intercity bus services, and larly the private ones. The presence of more private load carrying trucks. vehicles on the roads results in unwanted space A concise framework for a sustainable traffic manage- occupancy with lesser productivity. Due to wide ment system, ideally to be implemented in Faisalabad expansion of Faisalabad city along Satiana Road, city, in particular, and, generally, for any other place Jhang Road, Sargodha Road, Lahore Road, and with similar characteristics and traffic behaviour and Samandari Road, it is highly recommended to issues is represented in Figure 27. Subjected to Figure 27. Four roads to a sustainable transportation system in Faisalabad city. GEOLOGY, ECOLOGY, AND LANDSCAPES 15 establishment, this framework in Faisalabad city would Bashorun, J. O., & Olamiju, I. O. (2013). Environmental pollution and refinery operations in an oil producing lead to a sustainable transport management system in the region of Nigeria: A focus on warri petrochemical city and will reduce the air and noise pollution issues company. Journal of Environmental Science, Toxicology along with reducing the probability of accident occur- and Food Technology, 2(6), 18–23. https://www.iosrjour rence due to haphazard transportation, thus ensuring nals.org/iosr-jestft/papers/vol2-issue6/F0261823.pdf maximum road softy measures. Boateng, C. A., & Amedofu, G. K. (2004). Industrial noise pollution and its effects on the hearing capabil- ities of workers: A study from sawmills, printing press and corn mills. African Journal of Health Sciences, 1 5. Conclusion (12), 55–60. https://doi.org/10.4314/ajhs.v11i1.30778 This research work concludes that major spatial Clark, C., & Stansfeld, S. A. (2007). The effect of transporta- variations in noise levels were observed at DHQ tion noise on health and cognitive development: A review of recent evidence. 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Journal

Geology Ecology and Landscapes – Taylor & Francis

Published: Oct 2, 2023

Keywords: Sustainable transportation system; noise pollution; haphazard traffic; heavy traffic; geostatistical analysis; health impact

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