Assessment of Noise Pollution and Health Impacts of the Exposed Population in an Urban Area of Chhattisgarh, India

The present study aimed to evaluate the possible impact of noise pollution. This study was conducted in Raipur, the capital of Chhattisgarh state, India, to analyze the relationship between noise pollution and health complaints. A total of 18 locations were selected for monitoring noise pollution levels in the morning (9:00-10:30 AM) and evening (7:00-8:30 PM). Noise maps were prepared for both the time interval, and it was found that the highest equivalent noise level (L eq )of 81.31 dBA was observed at location L3 whereas the lowest L eq of 63.25 dBA was observed at L16 in the morning and in the evening 77.33 dBA at L3 and 60.14 dBA at L16 were observed. A questionnaire survey was performed on the population (n = 400) exposed to noise and analyzed through a variance-based partial least square (PLS) structural equation model (SEM). From the survey, it was found that most of the respondents are exposed to higher noise levels and are facing health issues of “pain in the ear,” “rise in blood pressure,” “loss of sleep,” “whistling and buzzing” in their ear, “headache,” “heaviness” and “efficiency problem.” A total of 109 hypotheses were proposed and analyzed through bootstrapping with a subsample size of 5000 in SmartPLS software. 18 hypotheses were found to be significant in the proposed model. SEM analysis revealed an interrelation between noise pollution and health effects. It is recommended that strict regulation in nearby sensitive areas must be imposed and an awareness drive on a large scale shall be conducted to enlighten the city’s population regarding noise effects as well as various measures for controlling.


INTRODUCTION
One of the invisible pollutants present in our environment is noise. Any disturbing or unwanted sound that affects the wellbeing and health of a human or any other organism is defined as noise pollution. Air and noise pollution are mainly generated by road traffic, which both affect human health (Stansfeld & Clark 2015). For the community noise, the main source is road traffic. It is well known to everyone that, mainly in larger cities, noise pollution is continuously affecting the exposed population (Wu et al. 2019). Major factors contributing to the higher environmental noise levels are increased rail, road, and air traffic, economic growth, and urbanization (de Souza et al. 2019, Ramanathan & Renuka 2008. The increase in noise levels on roads is mainly due to an increase in the number of vehicles, vehicles type and conditions, road quality, the density of vehicles, and weather conditions (Farooqi et al. 2019, Tabraiz et al. 2015, Gilani & Mir 2021, Hunashal & Patil 2011 Apart from this, festivals also contribute to higher noise levels in India. The Diwali festival is one of the major factors contributing to air and noise pollution throughout the country (Garg et al. 2017).
A large number of railway helps improve public transport but cause different harmful effects on the nearby population (Sarikavak & Boxall 2019). Noise from locomotives during idling or operation, bunching, and stretching wagons during braking or acceleration, and noise from the flanging of wheels on the curve is typical noise generated from the railways (Jiang et al. 2015). Electrified rail line causes less air pollution, but at the other end reduction in noise pollution is not observed. Noise from the tire can dominate other sources at 70km.h -1 speed of vehicles. Hence noise on the road can be mitigated by limiting the speed in streets in densely populated areas. If the road gradient is reduced by 5%, then 1.5dB of noise can also be reduced by plantations of trees can help in mitigating higher levels of noise. Similarly, reducing 10dB of noise construction of barriers along the road is recommended (Farooqi et al. 2019).
People with higher noise levels in surroundings significantly have higher noise annoyance and stress levels. Continuous exposure to higher noise levels causes permanent or temporary hearing loss. It can induce physiological effects (anxiety, depression), which can be permanent or temporary (de Souza et al. 2019, Al-Mutairi et al. 2011, Juang et al. 2010, Chakraborty & Banerjee 2007. It can also cause high blood pressure, irregular heartbeat, sleep disturbance, and lack of concentration and efficiency (Farooqi et al. 2020, Terry et al. 2021, Hahad et al. 2021). In the middle-aged group, self-reported hypertension and higher noise levels from road traffic are interconnected (Bodin et al. 2009). Noise also affects adversely to children by causing premature birth and low birth weight (Stansfeld &Clark 2015). According to the World Bank Population Report of 2019, India is the second largest country in terms of population worldwide (World Bank 2019). As per the Department of Economic Division (2019) United Nations, India will overtake China by 2027 in terms of population (UN 2019). As of 31 st March 2019, India also has 296 million registered vehicles, and an annual growth rate of 9.9 percent during the last ten years (2009 to 2019) was recorded (MORTH 2019). In Raipur, the total number of registered vehicles is 1.5 million, among which 1.4 million are non-transport vehicles and 0.13 million are transport vehicles as of 31 st March 2019. The number of registered vehicles in the city has increased by a very large number. The total number of vehicles registered in Raipur City from 2010 to 2019 is shown in Fig. 1, and the percentage of different classes of vehicles as of 31 st March 2019 is shown in Fig. 2.
People living near noisy streets and residential areas near highways and railways are most vulnerable to noise pollution. The exposed people mostly face difficulty in sleeping and get awakened at night, as a result of which they feel tired and have work efficiency problems mostly. Also, these populations have short and long-term effects due to higher noise levels (Ristovska & Lekaviciute 2013, Gholami et al. 2012. This study was designed to determine the impacts of noise pollution on the selected target population. Raipur City, the capital of Chhattisgarh state of India, is selected as the study site in the current investigation. To find the relationship between the demographic, physiological, and psychological factors of the exposed population in the study variance- People living near noisy streets and residential areas near highways and railways are most vu to noise pollution. The exposed people mostly face difficulty in sleeping and get awakened at n a result of which they feel tired and have work efficiency problems mostly. Also, these pop have short and long-term effects due to higher noise levels (Ristovska & Lekaviciute 2013, Gh al. 2012). This study was designed to determine the impacts of noise pollution on the selecte population. Raipur City, the capital of Chhattisgarh state of India, is selected as the study sit current investigation. To find the relationship between the demographic, physiologic psychological factors of the exposed population in the study variance-based structural equation (SEM) method is used. This work using SEM is conducted for the first time in the selected stu which makes it new and different. The previous study by Fhyri and Aasvang (2010) incorporat to find the relationship between traffic noise and heart problems. Also, SEM was used by Fy Klaeboe (2009) to explore the relation between noise from traffic, self-reported health on. The exposed people mostly face difficulty in sleeping and get awakened at night, as This work using SEM is conducted for the first time in the selected study area, which makes it new and different. The previous study by Fhyri and Aasvang (2010) incorporated SEM to find the relationship between traffic noise and heart problems. Also, SEM was used by Fyhri and Klaeboe (2009) to explore the relation between noise from traffic, self-reported health issues, annoyance, and sensitivity. Their study suggested a strong relationship exists between sensitivity to noise and health complaints. Variance-based Partial Least Square (PLS) SEM is mostly preferred over covariance-based (CB-SEM) by most researchers because of its different advantages (Ooi et al. 2018). PLS-SEM performance on a different scale is good, and like other multivariate analysis techniques, it thoroughly evaluates the results, makings it reliable in studying hypothetical theory (Hair et al. 2011(Hair et al. . 2012.

Description of the Study Area
The acoustic study was conducted in Raipur City of Chhattisgarh, India (1 st August to 15 th September 2022). The City is situated in the East Central part of the state at the latitude of 21 o 16'N, longitude 81 o 36'E with an altitude of 289.5m above mean sea level. Raipur is the capital of Chhattisgarh, with the highest population density among other state cities. As per the census 2011 of India, the total population in Raipur is 1,010,433, of which 518,611 are male, and 491,822 are female, respectively. The density of the city is 328 people per km 2 . The city's climate is subhumid, with an annual average rainfall of 1489mm, of which 1348mm is received during the monsoon season. Historically it has been found that wind speed in September was 6.8mph. Raipur is well connected to other cities of the state, and it has a wide road network. The city's road network and sampling locations are shown in Fig. 3.

Study Design
This study measured equivalent noise levels (L eq ) at major city squares and a questionnaire survey. Random sampling was used for the survey work. The sample size was determined using the formula 4pq.L -2 (Sahu et al. 2020). "p" was taken as 50% with a permissible error of 5%. A 95% confidence limit sample size was determined as 396, rounded to 400. Measurement of L eq was done both in the morning and evening. Noise maps were prepared using the inverse distance weighting (IDW) interpolation method in ArcGIS software. A survey was carried out on the determined sample size, and data were analyzed using PLS-SEM. The detailed methodology of the study is shown in Fig. 4.
of the city is 328 people per km 2 . The city's climate is sub-humid, with an annual average rainfall of 1489mm, of which 1348mm is received during the monsoon season. Historically it has been found that wind speed in September was 6.8mph. Raipur is well connected to other cities of the state, and it has a wide road network. The city's road network and sampling locations are shown in Fig. 3.

Study Design
This study measured equivalent noise levels (Leq) at major city squares and a questionnaire survey.
Random sampling was used for the survey work. The sample size was determined using the formula

Noise Measurement and Mapping
Noise levels were observed at 18 locations in the study area using Extech (Model: SL-400) sound level meter (SLM) during the morning (9:00-10:30 AM) and evening (7:00-8:30 PM). The instrument was mounted on a tripod and elevated to 1.5 m above the ground level. ISO 1996-1:2016 standard method was used for measuring noise at different locations (ISO 1996(ISO -1 2016. SLM was placed on the side of the road 2m from reflecting objects. L eq was recorded at each location, and an average value was obtained using statistical analysis. The latitude and longitude of each location were recorded and inserted in ArcGIS software to prepare the map. The average L eq of each location was used to perform IDW interpolation in GIS, and noise maps were prepared for each morning and evening, respectively.

Noise Measurement and Mapping
Noise levels were observed at 18 locations in the study area using Extech (Model: SL-400) sound level meter (SLM) during the morning (9:00-10:30 AM) and evening (7:00-8:30 PM). The instrument was mounted on a tripod and elevated to 1.5 m above the ground level. ISO 1996-1:2016 standard method was used for measuring noise at different locations (ISO 1996(ISO -1 2016. SLM was placed on the side of the road 2m from reflecting objects. Leq was recorded at each location, and an average value was obtained using statistical analysis. The latitude and longitude of each location were recorded and inserted in ArcGIS software to prepare the map. The average Leq of each location was used to perform IDW interpolation in GIS, and noise maps were prepared for each morning and evening, respectively.

Questionnaire Survey
Questionnaire surveys were conducted on the population (n = 400) exposed to high noise levels. The questionnaire was divided into different sections containing demographic information of the respondents, such as their age, gender, occupation, and duration of the exposed high noise levels. 6 point scale was used to get the response from the exposed population. "Rarely = 1", "Sometimes = 2", "Often = 3","Usually = 4","Never = 5," and "Always = 6" were the anchors to the questionnaire.
Respondents were asked to fill out the survey form based on their thinking over the last 12 months regarding noise pollution. Questions (Q1-Q17) to assess problems like sleeping, headache, pain in the ear, blood pressure, visualization, sweating, etc., were asked from the respondents. Based on the response received, statistical analysis was carried out to find the impact of noise on the exposed population of the study area. The questions that the respondents were asked are shown in Table 1.   Can you say that the high level of noise affects your health?

Q4
How often are you exposed to high noise in your daily routine?

Q5
Due to noise, do you feel pain in your ears after/while listening to music?

Q6
Is there whistling and buzzing in your ears when exposed to higher noise levels?

Questionnaire Survey
Questionnaire surveys were conducted on the population (n = 400) exposed to high noise levels. The questionnaire was divided into different sections containing demographic information of the respondents, such as their age, gender, occupation, and duration of the exposed high noise levels. 6 point scale was used to get the response from the exposed population. "Rarely = 1", "Sometimes = 2", "Often = 3","Usually = 4","Never = 5," and "Always = 6" were the anchors to the questionnaire. Respondents were asked to fill out the survey form based on their thinking over the last 12 months regarding noise pollution. Questions (Q1-Q17) to assess problems like sleeping, headache, pain in the ear, blood pressure, visualization, sweating, etc., were asked from the respondents. Based on the response received, statistical analysis was carried out to find the impact of noise on the exposed population of the study area. The questions that the respondents were asked are shown in Table 1.

PLS-SEM Hypothesis Development
To investigate the relationship between noise pollution and its effect on the following human hypothesis (HP) was proposed which is shown in Table 2.

Analysis of Data Through PLS-SEM
SEM path analysis is used in this study using Smart-PLS 3.0 software. SEM is expressed as a path model that estimates direct and indirect effects. SEM and path models are more advantageous and powerful than multiple regression models (Davvetas et al. 2020). A total of 109 hypotheses have been developed and examined. The hypothesis has been made by connecting demographical, physiological, and psychological factors. Bootstrap of the developed model was done, and results were obtained by taking 5000 subsamples. The developed model is shown in Fig. 5.

Noise Pollution Monitoring and Mapping
This study included 18 locations for monitoring noise pollution in the morning and evening. Fig. 6 & 7 depict the noise map of the study area, respectively. Table 3 depicts the locations' detail and the observed average L eq for both intervals. A better understanding can be developed by noise map compared to tabular form. The above-mentioned figure reveals that all the locations have a higher level of noise in the environment. A road network with high traffic volume  surrounds all the locations. The Highest L eq of 81.31 dBA was observed at location L3, whereas the lowest L eq of 63.25 dBA was observed at L16 in the morning.
Consequently,77.33 dBA at L3 and 60.14 dBA at L16 were observed in the evening. All the locations breached the ambient standard noise level prescribed by the Central Pollution Control Board (CPCB), New Delhi. While studying, it was found that in the morning, 0% of the locations had noise levels less than 50 dBA, 44.46% fell between 60 to 70 dBA, 33.34% between 70 to 75 dBA, and 22.23% above 75 dBA.
Similarly, in the evening, 0 % below 50dBA, 27.78% between 60 to 70 dBA, 38.8% between 70 to 75 dBA, and 33.34% above 75 dBA, respectively. The noise levels' results are close to those obtained in Delhi City by Mishra et al. (2021). In his study, the morning noise levels varied between 68.5 to 80.4 dBA, whereas evening varied between 71.9 to 83.7 dBA. Pathak et al. (2008) studied Varanasi city of India and found a maximum noise level of 75.3 dBA in their study location. Similar to other studies in India, our results reveal that Raipur is also facing the problem of noise pollution, and exposed people are affected by it.

Questionnaire Analysis
This study included 400 respondents in the questionnaire survey. 73.84% of the respondents were male, whereas 26.16% were female. The average age of the respondents is 30.7 ± 10.69 years. The response analysis was carried out in two phases, one for overall response and the other for a response based on age group. Fig.8 depicts the overall response, whereas Fig. 9 depicts the response in the age group. The questionnaire revealed that respondents suffer from disturbing noise in their workplace or residence. 31.28% of respondents considered "sometimes" they are exposed to a high level of noise, followed by 24.10% "usually," 20.14% "often," 13.34% "always," 9.74% "rarely," and 1.53% "never." Respondents also considered high noise affected their health and caused different physiological and psychological effects. 32.30% of considered pain in the ear "sometimes," followed by 21.53% "never" and 18.97% "often." Consequently, 22.05% reported whistling and buzzing, and 28.71% had interference with the speech in the ear "often." As per the survey report, 34.35%, 28.71%, and 33.34% of the respondents "sometimes" suffer from annoyance, efficiency problems, and sleep loss, respectively. However, 60.51%, 51.79%, and 40.10% "never" suffered from visual disturbance, giddiness, and a rise in blood pressure due to higher noise levels but 12.30%, 19.48%, and 28.20% "sometimes" suffered. 21.5% "often" felt headaches and heaviness due to noise, while 25.12% agreed that their friends say they are habitual debaters. A similar study by Swain & Goswami (2013) in Baripada, India found that due to noise, 41 % of respondents were annoyed, 11% had a loss India and found a maximum noise level of 75.3 dBA in their study location. Similar to other studies in India, our results reveal that Raipur is also facing the problem of noise pollution, and exposed people are affected by it. Fig.6: Noise map of morning noise levels   of sleep, and 34 % identified headache as a major problem.
A similar response was found in a study by Pathak et al. (2008) and Murthy et al. (2007).
The survey result is analyzed based on age group. It is found that 53.84 % of the respondents below 20 years accept that "sometimes" noise pollution is present in their environment, and 76.92 % feel that noise is affecting their health. Problem-related sleep loss ranges from 30-37 % in the age groups<20, 21-30, and 31-40. This might be because this age group mostly moves around for work, study, and other activities and gets exposed to a higher level of noise. Visual disturbance and sweating have been reported very less This publication is licensed under a Creative Commons Attribution 4.0 International License by this age group. The rise in blood pressure due to noise in the age group 41-50 is 47.36% "sometimes." All the other effects of noise in the age group are shown graphically. The response of the respondents is shown in Table 4. Fig. 8: Self-reported health complaints by the overall exposed population (in Percentage).    Furthermore, Pearson correlation was measured between the responses received to study their strength of association. Table 5 depicts the correlation result among the survey responses. 12 coefficients were found in a range of 0.30 to 0.49, which states that moderate relation is found between them. Consequently,6 coefficient values were found nearly to 0.5, revealing a strong correlation.

Response Analysis Through PLS-SEM
Based on the result of the questionnaire SEM model was prepared to find the path coefficient and study the relation between the different effects of the noise on the exposed population. The prepared model using Smart PLS software is shown in Fig. 5. After bootstrapping, the result shows that 18 hypotheses are supported. The t statistics value greater than 1.96 is taken as supporting, whereas less than that value is rejected. The result of the SEM analysis is shown in Table  6. The HP1, HP2, HP20, HP38, HP39, HP40, HP41, HP55,  HP56, HP57, HP65, HP75, HP83, HP84, HP87, HP88, HP92 and HP96 are found to be significant. From the significant hypothesis, respondents who agreed that noise pollution in their area are facing health issues like pain in the ear, rise in blood pressure, loss of sleep, whistling and buzzing in their ear, headache, heaviness, and efficiency problem. Also, an association between exposure time and noise affecting health is found to be significant in this study. Seidler et al. (2017) found that exposure to traffic noise results in depression. A similar study on the health effect of noise was carried out by  Martin et al. (2006), and Kjellberg et al. (1998) found that headache and fatigue are the two most commonly reported health issues by the respondents. According to Ismaila & Odusote (2014), multiple articles have reported health issues related to traffic noise exposure and blood pressure.
Higher-paid people are less exposed to noise pollution than the lower-paid (Kjellberg et al. 1996); hence strong significance is found in our study between "occupation and 4 other questions". Thus this study reveals that the population of Raipur City faces the above-mentioned health issues due to high noise levels. The population exposed to traffic noise is mostly affected by noise and faces the health issues mentioned above.

CONCLUSIONS
Noise pollution monitoring and mapping in the current study revealed that all 18 locations recorded higher noise levels and breached the ambient noise standard of CPCB. Hence the governing bodies must implement mitigating approaches for controlling it as higher levels cause different health problems among the exposed population of the city. From the survey study, it is found that most of the respondents are exposed to higher noise levels and are facing health issues of "pain in the ear," "rise in blood pressure," "loss of sleep," "whistling and buzzing" in their ear, "headache," "heaviness" and "efficiency problem." It can be concluded that the exposed population of the city is highly affected by noise pollution. SEM analysis reveals an interrelation between noise pollution and health effects. The association between exposure time and noise affecting health is significant in this study. The study gives ample evidence that higher noise levels in the study area are present and the population is highly affected; hence study supports the importance of making guidelines in context to mitigating approaches. The study recommends making strict regulations near the most sensitive areas like hospitals, schools, and residential areas to ensure a good and healthy environment in the city. Environment and health agencies must conduct awareness drives on a large scale and keep enlightening the city's population regarding noise effects and various measures for controlling the higher noise levels in the ambient environment.