Urban Noise Pollution Assessment and its Non-Auditory Health Effects on the Residents of Chiniot and Jhang, Punjab, Pakistan

Noise pollution is an emerging global problem therefore, it is imperative to determine noise level especially in the urban environment and its implications on human health. The objectives of this study were i) to assess the urban noise pollution and trac density of Chiniot and Jhang and ii) to determine non-auditory health effects of noise pollution on the residents of both cities. Noise pollution was examined from 181 locations (103 from Jhang and 78 from Chiniot) and categorized into hospitals, educational, religious and recreational, residential, industrial areas, and trac intersections. Noise levels measurements were taken using integrated sound level meter. The urban noise data showed 82% of the sites in Jhang and 95% in Chiniot exceeded the noise limits set by NEQS-Pak and WHO. Moreover, higher intensity of noise pollution ( ≥ 100 dB) was recorded in Chiniot (17 sites) than in Jhang (1 site). Regression analysis showed relatively strong relationship of trac density with noise at Chiniot (R 2 = 0.48) compared to Jhang (R 2 = 0.31). However, spatial variability of noise with trac density was observed at both cities. Survey study revealed that all the respondents in Jhang and Chiniot suffered from many noise related health problems such as annoyance (53 and 51%), depression (45 and 47%), dizziness (61 and 65%), headache (67 and 64%), hypertension (71 and 56%), hearing loss (53 and 56%), physiological stress (65 and 65%), sleeplessness (81 and 84%), and tinnitus (70 and 62%) due to noise, respectively. It is concluded that noise pollution is higher in Chiniot due to high trac density resulted from higher population density and cottage industry. It is recommended that vehicles maintenance, family and urban planning could be effective measures to reduce urban noise pollution. and noise-borne non-auditory effects assembled from both studied areas (Jhang and Chiniot). The age shows a variable response to noise-borne non-auditory health effects at both areas. Age caused signicant positive effects on headache (r = 0.27, P < 0.01) in the residents of Jhang, while headache (r = 0.58, P < 0.01), depression (r = 0.28, P < 0.01), hypertension (r = 0.46, P < 0.01), physiological stress (r = 0.34, P < 0.01) in the residents of Chiniot. The negative correlation of sex found with depression (r= -0.26, P < 0.01), hearing loss (r= -0.25, P < 0.05) while positive with physiological stress (r = 0.20, P < 0.05). The correlation results revealed that depression caused dizziness (r = 0.31–0.38, P < 0.01) and headache (r = 0.36–0.76, P < 0.01) in the residents of Jhang and Chiniot. annoyance correlation revealed that age had positive impacts on noise-borne non-auditory health effects in humans especially headache, depression, hypertension, and physiological stress are directly related to age, however, hearing loss due to noise is more common in children (Table Moreover, noise-borne non-auditory health effects are found in both males and females indicating these effects are independent to gender. Pearson product moment correlation results inferred spatial impacts of noise-borne non-auditory health effects on the residents of both areas. Our presented results are in line with some of the previous studies conducted in other cities and geographical zones of the world (Table 7); as multiple studies have described the negative impact of noise levels on the nearby community, citizens, patients and students in the study areas. These results also indicate that there is a signicant relationship between the trac density and the urban noise levels.


Introduction
The urban noise pollution is recognized as a major problem for the quality of life in metropolitan cities all over the world (Ozer et al. 2009;Fredianelli et al. 2019). As an important environmental element with social and aesthetic attributes, the quality of soundscape is one of the most important factors for environmental perception (Brown and Muhar 2004;Kang 2006;Yong et al. 2011;. Noise is mainly produced from industrial processes, tra c vehicles, railway, air tra c, construction and domestic noise (Braat-Eggen et al. 2017;Fedorko et al. 2018;Hahad et al. 2018). Noise pollution is primarily increased due to increase in the number of vehicles on roads, however, there are many factors manipulating the level of tra c noise such as car type and their condition, quality of roads, vehicles density and their physical state, and weather conditions etc. (Wolniewicz and Zagubień 2015). The buildings with low sound insulation have higher level of environmental noise (Ng and Hui 2008;Paiva et al. 2019). It is annoying and disturbing people in their daily life activity (Auger et al. 2018;Javaherian et al. 2018;Mahmud et al. 2019;Farooqi et al. 2020). Normal people can bear the noise up to 80 dB and it may damage the nerves directly if it exceeds that limitation (Purwaningsih et al. 2018). It is thought that the excessive noise levels in the urban environment is due to the industries (Bamane et  . It was observed from the previous studies that many sites in Faisalabad, Pakistan have SPLeq > 100 dB, which were exceeding the permissible limits of Pakistan Environmental Protection Agency (Farooqi et al. 2017). Urban noise is not only the issue in Pakistan, but also in most parts of the world. In seven major cities of India, majority of sites ranged noise level between 75-90 dB in commercial areas while the limits were 65 dB, 67-93 dB in industrial zone against the limit of 75 dB, 75-85 dB was recorded in residential area against 55 dB, and 60-90 dB range was recorded in silent zones against the limits of 50 dB (Garg et al. 2016). Same patterns of urban noise pollution were reported in London (Tonne et al. 2018), and up to 110 dB noise levels were recorded in subways in Hong Kong which were exceeding the permissible levels of 70 dB set by WHO (Xu et al. 2019). It is also reported that urban noise signi cantly affect the property prices by 24. 4% (Zheng et al. 2020). The main causes of urban noise are the industries and their processes (Liu et al. 2019;Farooqi et al. 2020), and increasing tra c density in the cities due to population increase growth. Tra c vehicles use horns openly which cause noise more than the industrial processes does . Increased noise levels due to tra c causes different human health interventions like hypertension (Hahad et al. 2019;Nassiri et al. 2019 In Pakistan, the urban noise is affecting the citizens health with the same pace, but the noise levels and their effects are not studied in most cities in the country. Therefore, the present study was conducted i) to assess the urban noise pollution and tra c density of Chiniot (new civilization) and Jhang (old civilization), ii) survey-based assessment of non-auditory health effects of noise on the residents of both cities and iii) production of baseline data in the form of geographic maps through modern software technologies (ArcGIS and XLSTAT) for Government considerations and public awareness. This study could also help Govt. agencies in decision making for management of noise pollution and its health impacts on residents of targeted cities.

Geo and Demo-graphic features of study area
Jhang and Chiniot are the developing cities of Punjab, Pakistan. Chiniot was a tehsil of District Jhang but now it is independent District of Punjab.
The Chiniot is densely populated (524.9 persons/km 2 ) as compared to Jhang (431.9 persons/km 2 ). According to recent census in 2017, Jhang has 2.74 and Chiniot has 1.36 million populations with the increasing rate of 2.04 and 1.36%, respectively (Table 1). Consequently, urban noise is increasing day by day. Tra c density is the main factor which contributes to increasing urban noise. More than 63% (Jhang) and 68% (Chiniot) of passenger's travel within these cities using motorbikes, cars, and buses, which are the signi cant factors to produce noise and in uence inhabitants. This study compiles the basic data about urban noise pollution, tra c density and its impact on residents of both cities. Figure 1 describes all the sampling locations for urban noise pollution determination of Jhang (green) and Chiniot (yellow) cities.   (17), commercial places (13), educational institutes (12), hospitals (10), residential areas (10), religious and recreational areas (10), and industrial areas (7) (Fig. 1). The measurement and evaluation of noise levels were performed in compliance with the national legislation of Pak-EPA (Iyer et al. 2017). Noise levels were measured by placing SLM at tripod at the level of 1.7 meters from the level of the pavement, distance of 3 meters from the noise re ecting surface. The intensity of noise was measured in afternoon one by one at selected areas for 15 min per reading per location (near the receivers) by using SLM. The sound level was measured as A-weighting using SLM model TES-1351B type 2 with a frequency range of 20-8000 Hz and accuracy of ± 1.0 dB (94 dB @1 kHz). The SLM was calibrated by the internal oscillator at the rate of 1 kHz sine wave general (94 dB) (Farooqi et al. 2020).

Tra c density measurement
Tra c density was measured as the number of vehicles/h that occupied a segment of a road (Farooqi et al. 2020). The tra c density was calculated as number of vehicles/h by simple calculation as described by Paunovic et al. (2013) in which the number of vehicles was counted for 15 minutes at each location simultaneously with noise levels recording.

Questionnaire based survey
A questionnaire-based survey study was also conducted from the sampling locations of both cities to evaluate the non-auditory human health impacts of noise pollution. Further, to get better perception of noise impacts on human health, a questionnaire was lled by four age groups (≤ 20, ≤ 40, ≤ 60, ≤ 80 years) and their response was recorded in the form of "Agree", "Disagree" and "No comments". In addition to basic questions of health effects of noise, respondents were also asked about time of the day (Morning, Evening, After-noon, don't know) when there might be maximum noise pollution.

Statistical analysis
The collected data was analyzed as descriptive statistics. Pearson correlation analysis was performed to determine correlation between tra c density and noise levels. Moreover, Pearson product moment correlation was performed to determine the effect of age and sex on non-auditory health effects on the residents due to noise, and between the non-auditory health effects. ArcGIS software (version 10.4.1) was used to produce the maps and categorization of noise levels and tra c densities in the study areas.

Noise levels in Chiniot and Jhang
The descriptive statistics of noise pollution and relevant tra c density of various places of Jhnag and Chiniot are presented in Table 2. The maximum noise level (dB max = 103 with dB ave = 88) was recorded at educational institutes followed by tra c intersections (dB max = 102 with dB ave = 86) in Jhang whereas in Chiniot maximum noise level (dB max = 120 with dB ave = 89) at commercial places followed by tra c intersections (dB max = 115 with dB ave = 93). About 95% (74 out of 78) of the sampling locations in Chiniot and 82% (84 out of 103) locations in Jhang showed noise levels exceeding the permissible limits set by National Environmental Quality Standards (NEQS), Pakistan.  (Table 4S). Figure 3 describes noise intensity at each main location of Chiniot and Jhang urban areas. Industrial areas of both cities showed noise intensity in the range 80-100 dB, however, few places showed noise level under the permissible limit (75 dB) set by NEQS-Pak. Tra c intersections of both cities showed noise intensity of < 80, 80-100 and > 100 dB (Fig. 3), only three places in Jhang and two places in Chiniot have noise level within permissible limit of 70 dB (Table S3). The commercial area of Chiniot showed nosie level of < 80, 80-100 and > 100 dB whereas Jhang showed noise within 80-100 and > 100 dB. The educational institutes, hospitals, residential, religious, and recreational areas of both cities had noise level within 80-100 and > 100 dB, however, few samples in residential area of Chiniot showed noise level > 100 dB.

Relation between noise levels and tra c density (T f )
Linear regression analyses were performed to determine effect of tra c density on noise pollution. Results revealed that tra c density is directly related to noise pollution, however relation was weak at Jhang (R 2 = 0.31; Fig. 2a) compared to Chiniot (R 2 = 0.48; Fig. 2c). The relationship of tra c density and noise pollution varied with receiving community and showed a spatial variability. The regression analysis revealed strong linear relation between tra c density and noise pollution at hospitals (R 2 = 0.79), residential areas (R 2 = 0.77), whereas weak at industrial areas (R 2 = 0.44), religious and recreational areas (R 2 = 0.32), commercial places (R 2 = 0.17) in Jhang (Fig. 2b). Similarly, strong linear relation between tra c density and noise pollution was found at commercial places (R 2 = 0.85), tra c intersections (R 2 = 0.77), religious and recreational areas (R 2 = 0.61), hospitals (R 2 = 0.53) and educational institutions (R 2 = 0.50) in Chiniot (Fig. 2d).
The respondents of four age groups were interviewed about the speci c times (morning, afternoon, evening, don't know) when they are exposed to maximum level of noise (Table 5). Out of 400 respondents in Jhang, 195 people (48%) responded that they were exposed to maximum noise at afternoon timings. This might be due to the high tra c at school-off timing, 104 (26%) said that they were exposed to high noise at morning time and 67 people (17%) told that they were exposed to maximum noise at evening timings while 34 people (9%) gave no response. Similar response was obtained in Chiniot where, out of 400 respondents, 223 respondents (56%) were exposed to maximum noise level at afternoon timings. It was attributed to the high tra c due to school-off timing, 92 respondents (23%) told that they were exposed to high noise at morning time and 54 (14%) told at evening timings while 31 people (7%) gave no response. According to the above results, the citizens of both the cities were exposed to maximum urban noise levels during afternoon time with the order afternoon > morning > evening.

Discussion
Noise pollution is an emerging threat to developed and under-developed countries, therefore, it is obvious to collect baseline data for effective management of expanding urbanization. Here, in this study, we have tried to determine noise intensity at various gathering places of Jhang and Chiniot urban areas. In both the study areas, we found that most of the sites exceeded the SPL limits prescribed by the NEQS-Pak and WHO (Table 2). Chiniot to all over the country. These dumpers are not usually seen in Jhang. Another reason is the central position of Chiniot, which facilitates movement of heavy tra c to Lahore, Faisalabad, Sargodha and Jhang. Chiniot city is the hub of small industry, stone crushing industry and wood artwork, therefore, many people visit this city on frequent basis for business purpose which increases tra c frequency and thus high noise pollution. The industries are signi cant source of noise pollution, which is increased with increase in the industrial processes (Kannan et al. 2017;Deb et al. 2018;Kim et al. 2019). The high level of noise in Chiniot is due to working of small industry and our results revealed that negative correlation (R 2 = 0.04) existed between noise level and tra c frequency in industrial set up of Chiniot (Fig. 2d), which conferred that tra c did not the source of noise rather industrial operations might be the possible reason. The dense population per unit area in the city (Table 1) is also the reason behind high noise.
Govt. should take stringent action to control population growth rate in both cities, ensure maintenance of vehicles and ban on pressure horns in urban areas. Based on the noise level readings of every area category, we divided them into equal intervals (40-50, 51-60, 61-70, 71-80, 81-90 and ≥ 90). Only 5 areas (1 residential and 2 both in hospitals and religious and recreational areas in Jhang) were lying in 40-50 dB category and most of the areas (n = 25) lying in above 90 dB category. Even worse condition was seen in Chiniot where no site had noise levels between 40-50 dB while only 1 site lied in between 51-60 and above half (n = 32) were lying in areas with more than 90 dB noise levels (Table 6). Non-auditory impact of noise pollution on public health is obvious. Survey study revealed that all the respondents in Jhang suffered higher level of annoyance, headache, hypertension, and tinnitus than residents of Chiniot due to noise, however, depression, dizziness, hearing loss, physiological stress and sleeplessness were higher in residents of Chiniot than Jhang (Table 3) . The Pearson product moment correlation revealed that age had positive impacts on noise-borne non-auditory health effects in humans especially headache, depression, hypertension, and physiological stress are directly related to age, however, hearing loss due to noise is more common in children (Table 4). Moreover, noise-borne non-auditory health effects are found in both males and females indicating these effects are independent to gender. Pearson product moment correlation results inferred spatial impacts of noise-borne non-auditory health effects on the residents of both areas. Our presented results are in line with some of the previous studies conducted in other cities and geographical zones of the world (Table 7); as multiple studies have described the negative impact of noise levels on the nearby community, citizens, patients and students in the study areas. These results also indicate that there is a signi cant relationship between the tra c density and the urban noise levels.

Conclusion And Recommendations
Tra c noise from a city street can affect the quality of life in noise-sensitive locations. This study revealed that tra c and industrial operation are the two main sources of noise in both studied cities, however the impact was higher in Chiniot (> 95% sampling locations) than Jhang (> 82% sampling locations) exceeding the permissible limits set by NEQS-Pak. The tra c density is directly proportional to noise pollution (R 2 = 0.50-0.85 in Chiniot while R 2 = 0.17-0.79 in Jhang). The survey-based results conferred health impacts of noise pollution on residents of both cities. Keeping in view the psychological and physiological health effects of urban tra c noise, reduction of exposure to noise is an important public health measure. There are several ways to avoid or minimize noise impacts to the maximum extent practicable. The best way to minimize exposure to a noise for new objects is to establish the zoning during planning and designing processes with relevant distance between a source, and building, as a recipient of noise. Tra c sources of noise and noise-sensitive population are normally incompatible unless effective measures are taken to reduce environmental noise. The compatibility depends on a good sound insulation of buildings. Noise from the outer lining of the building must be planned and implemented so that the noise level does not exceed the permissible limits. In environments, where noise effects cannot be readily reduced to a level of less signi cance by acoustical improvements, noise avoidance and mitigation measures of an existing building may be put in place directly with different noise barriers.
As vegetation provides noise attenuation, it can in uence noise impact potential for existing situation of noise. In this case, a plant material is economically, aesthetically, and psychologically the most suitable for the better acoustical performance of the buildings. The proposed measures ensure acoustic comfort and health for all the occupants of the buildings. At the end, there should be incorporation of appropriate preventive measures to minimize the noise impacts, as required under Pak-EPA and WHO recommendations.

Competing interests
The authors declare that they have no known competing nancial interests or personal relationships that could have appeared to in uence the work reported in this paper.

Ethics approval and consent to participate
This study does not involve any humans or animals during experimentation, so it does not applicable in this study.

Consent for publication
Survey was conducted in local community of both cities and questionnaire was lled with their verbal consent.