case study on noise pollution in malaysia

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Case Spotlight: Noisy Nightmare Neighbours

by Donovan & Ho (BD) | October 26, 2020 | Dispute Resolution

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The Covid-19 pandemic has kept most of us at home, most of the time. During the Movement Control Order in place earlier in the year, many renovations and/or construction were also halted. It is therefore no surprise that some may be experiencing increased levels of noise from their neighbours, including renovation noise.

For those who may be wondering about their rights when it comes to putting up with excessive levels of noise, the Court of Appeal decision in Chin Moy Yen & Ors v Chai Weng Sing & ors [2019] MLJU 681 on the tort of nuisance is worth looking into.

Brief facts  

A family of 7 (“ the Chans ”) residing at the Flora Green Condominium (located near Universiti Tunku Abdul Rahman) commenced action against the past and (then) present proprietors of 3 adjacent units directly above the Chans’ unit (“ Units ”).

The Chans’ case is that the Units were illegally renovated without proper approval from the authorities. The Units were partitioned and turned into student accommodations, with each unit renovated to extend the number of occupants to twice the usual amount.

These renovations went on frequently throughout the night and in the early hours of the morning. The renovations also caused physical damage to the Chans’ unit (cracks on the walls and ceiling, water leakage etc), and caused excessive noise and vibrations. The student tenants which later moved into the Units further contributed to the noise.

The management corporation of Flora Green Condominium were also named as a defendant for failing to discharge its duties and responsibilities as a management corporation under the Strata Management Act 2013.

Decision of the Court

The High Court dismissed the Chans’ claim finding that it was not proven. The High Court Judge found that there was not enough evidence of nuisance or trespass and held the registered owner/landlord, having not participated in any alleged act of nuisance, cannot be liable for any nuisance created by the tenants.

On appeal, the Court of Appeal reversed the decision of the High Court holding, amongst others:

• The renovations which caused water seepage or sewage effluent flowing from the Units as well as cracks to the walls in Chans’ units amounted to trespass
• The allegation of nuisance by reason of noise and disturbance generated by the activities of the occupants were corroborated by multiple police reports, warning notices issued by the local authorities and complaint emails by other residents to the management corporation. There is no necessity to prove by way of scientific or technical evidence that the noise generated was beyond tolerable levels
• Testimonies of 22 witnesses also confirmed the noise nuisance. One neighbour gave the following evidence:

“ overcrowded with students … and the students create a lot of noise and there were renovation noises as well ” “ sounded like dragging of furniture or something very heavy that fell on the floor late at night until early in the morning ” “ noise was loud enough to wake my wife and I up from our sleep ” “ noises I heard from C-P-1 were very loud ”

• The complaints were not imagined but were real; the noise and nuisance created not just by the renovations but by the residents in the Units were of such volume, intensity, persistence or regularity that by any reasonable standard this would be considered a nuisance
• Regard is given to the type of residence (namely, residential condominium)
• The proprietors/landlords of the Units though were not participants of the acts of nuisance by its tenants, were fully aware of the nuisance complained of and had taken no steps whatsoever to stop and/or reduce the complained nuisance. Therefore, the proprietor/landlord was liable for the nuisance created by their authorised tenants
• The statutory regime established under inter alia the Strata Management Act 2013 and the Regulations, Bylaws and House Rules enacted or passed under the Act bind all parties. The 3rd Schedule of the Regulations made under the 2013 Act, provides that residents “ shall not use or permit to be used his parcel in such a manner or for such a purpose as to cause nuisance or danger to any other proprietor or the families of such proprietor ”; “ or to use their respective parcels contrary to the terms of use. ” The effect of these statutory provisions is to recognize the common law duty of care with regard to neighbours in communal living, casting on all owners including the management corporation, the duty and responsibility of ensuring that there is no nuisance
• Ultimately, the Chans were awarded RM 80,000.00 in damages:
• RM 50,000 to be paid by the 1st respondent, who owned all the Units at different points in time;
• RM 20,000 to be paid by the 2nd to 4th respondents, who were the other proprietors of the Units;
• RM 10,000 to be paid by the 5th respondent, the management corporation of Flora Green Condominium

Key Takeaways

The decision is a good reminder that:

• As neighbours, whilst some level of noise is expected, there is a limit. Consideration for others must be practiced even when using and enjoying your own home.
• As landlords, liability is not absolved simply because the tort is committed or caused by third parties (namely, the tenants).
• As the joint management body or management corporation, mere investigations and taking steps to resolve complaints (or in other words, not completely ignoring or neglecting the complaints) is insufficient. There is a duty and responsibility to uphold the Regulations, Bylaws and House Rules enacted.

This article was written by  Donovan Cheah and Yan Nie Th’ng . Donovan is an Advocate and Solicitor of the High Court of Malaya. He is a Fellow at the Singapore Institute of Arbitrators, the Malaysian Institute of Arbitrators, and the Asian Institute of Alternative Dispute Resolution. He is also a registered foreign lawyer with the Singapore International Commercial Court.  

Donovan & Ho is a law firm in Malaysia. Our practice areas include employment law, dispute resolution, tax advisory and corporate advisory.  Have a question? Please  contact us .

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Home > Books > Noise Control

Impact of Noise Pollution during Covid-19: A Case Study of Balasore, Odisha

Submitted: 24 February 2022 Reviewed: 22 March 2022 Published: 13 May 2022

DOI: 10.5772/intechopen.104607

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Noise Control

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Activities such as development of industrialisation, urbanisation is a part of our life in the present scenario. During this phase we face a lot of health issues due to noise pollution. Growing of vehicle traffic is one of the major causes towards noise pollution and it affects significantly on the environment. The impact of such pollution had been assessed in 20 major squares (Commercial, residential and silence area) of the Balasore town during and after lockdown imposition of Covid-19. During lockdown period, the noise level of the town was within the permissible limit set by CPCB while before and after lockdown period it was beyond the permissible limit. The demographics and psychophysiological (annoyance, sleeping problem, tiredness, headache, and depression) responses of the participants were collected using standard questionnaires. It was also observed that there were better health conditions among the public (150 participated in the questionnaire) during the lockdown period, then before and after the lockdown phase. It was revealed that socio-demographic factors have no effects on the annoyance level.

• noise pollution
• health issues
• equivalent noise level

Author Information

Bijay kumar swain *.

• DIET, India

Chidananda Prasad Das

• Environmental Science Program, Department of Chemistry, ITER, S ‘O’ A Deemed to be University, India

Shreerup Goswami

• PG Department of Geology, Utkal University, India

*Address all correspondence to: [email protected]

1. Introduction

One of the most common job-related occupational risks is noise and is a global problem. In urban areas it affects the health of people and also the environment. In many reports it has been reported how the people from different part of world are exposed and affected by noise pollution [ 1 , 2 , 3 , 4 ]. Many studies also reported that there is a corelation between noise and health problems like headache, irritability etc. [ 5 , 6 , 7 ]. The main source of noise pollution is vehicular traffic noise or road traffic noise, as reported by many studies [ 3 , 8 , 9 , 10 , 11 , 12 ]. Increased noise exposure is known to produce annoyance [ 5 , 13 , 14 ], headaches [ 15 , 16 , 17 , 18 ], diabetes [ 19 ], irritability [ 20 ], sleep disturbances [ 21 , 22 , 23 , 24 , 25 , 26 ], hypertension [ 27 , 28 , 29 , 30 ], and problem in blood pressure [ 31 ]. Presently, it is a global problem [ 32 ].

Again, in many studies, it was also reported about the noise pollution level and its impact on public in world-wide [ 33 , 34 , 35 , 36 ]. Similarly, in many parts of India, research has been going-on on noise pollution and its impact on human health. In most of the study, it also been reported that the noise levels on Indian road conditions was more than the prescribed noise level set by CPCB [ 37 ]. The noise levels of many towns of Odisha are also more than the prescribed limit [ 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 ]. Silence zones were the most affected by noise pollution, according to Kalawapudi et al. [ 53 ], followed by residential, business, and industrial zones. They went on to say that proper city design could help people avoid being exposed to growing noise pollution levels, in Mumbai Metropolitan region. Thakre et al. [ 54 ] also discovered a 4.4 and 5.2 dB increase in the morning and evening sessions, respectively, in Nagpur from 2012 to 2019 [ 54 ]. The impact noise on bus driver [ 9 ], public coming to the park for refreshment [ 10 ], Office [ 55 ], Bank [ 56 , 57 ], festivals [ 11 , 41 ], Industrial areas [ 58 , 59 ] and workers working in the stone crusher industry [ 60 , 61 ] has also been reported. Zambon et al. [ 62 ] reported about the comparison to the same period in 2019, noise levels in terms of both absolute noise levels (Lden) and hourly noise profiles (median across lockdown period) showed a substantial drop of nearly 6 dB [ 62 ], while it was 1–3 dB in Boston metropolitan areas of USA [ 63 ] and reduction of 5.1 dB in Ruhr area of Germany [ 64 ]. The highest sound levels were found along major roadways, with a logarithmic reduction as distance from the roads increased [ 63 ]. Significant outdoor noise fluctuations were discovered, and participants clearly perceived noise variations both in urban and indoor settings, claimed by Caniato et al. [ 65 ]. Alias and Alsina-Pages reported that there was a significant reduction in the harmful impact of noise on the population of Milan urban and Rome suburban areas [ 66 ].

Now, most of the Indian cities are going to face major threats in the form of noise pollution on public’s health. It can affect both physically and mentally on the public’s health. But the life changed after the spreading of COVID-19 in whole world. After its existence, first Janata Curfew was coming in to existence followed by the lock-down system. During this period the vehicular traffic noise has been reduced drastically in world-wide. But how much it was reduced is a concern. In this study, an attempt has been made to access the noise levels of the Balasore town before, during and after lockdown phase in different areas. The impact of such noise levels on public’s health was also accessed through questionnaire. Suggestive reduction procedures are also given in the present study.

2. Methodology

2.1 study area.

Balasore is one of the famous districts in the state Odisha and situated in the eastern part of the state. It is famous for its cultural heritage, vast sea-beach and many more. It is also famous for Chandipur Sea Beach. The study area is the district head-quarter. As per 2011 census of India, Balasore District has a population of 2,320,529 in 2011 but estimates as per aadhar uidai.gov.in Dec 2020 data as 2,645,403. But the population of the municipality/metropolitan areas was 1,77,751 and city had 1,18,162. The latitude and longitude of the district is 21 29 39 North, 86 55 54 East respectively ( Figure 1 ). The monitoring town has elevation of 16 m. the maximum and minimum temperatures are observed to be 31.8 and 21.9 respectively, with an average rainfall of 1706.1 mm, average relative humidity of 71% and speed of 11 km/h. The research area is about 194 km away from the state capital. Different rural roads are connected to this town. Thousands of vehicles along-with number of heavy vehicles are flowing on different roads of the town. The town has a very wide commercial areas and lot of people from different regions were depending on this market for their daily needs. The major road of the town also connected with the Chandipur beach, and other religious areas of the district. Thus, heavy rush in vehicle flow has been shown on the town. Every day, thousands of different cars enter and exit the city. The metropolitan environment has a diverse traffic flow. It is one of the busiest municipalities/towns of the state, with a variety of land-use patterns.

Map of India showing the location area of the study area.

Nationwide lockdown (21 days) imposition in India was implemented between 25th March 2020 and 14th April 2020 as Phase 1 and between 15th April and 3rd May 2020 as Phase 2, Phase 3 from 4th May 2020 and 17th May 2020 and last phase (Phase 4) 18th May 2020 to 31st May 2020. Before this nation-wide voluntary public curfew was implemented on 22nd March 2020 for a time period of 14-hour. The same process of lockdown was also implemented in the Balasore town accordingly. Only essential good services are provided to the public. The Unlock phases was came into exist. The first unlock 1.0 came in to exist between 1st June to 30th June 2020. After the month of June 2020, the unlock phases was going on from unlock phase 1 to unlock 21 (1 February 2022 to 28 February 2022). In the present study, the noise levels recorded during unlock phase 1.0 and 2.0, i.e. 1st June 2020 to 30th June 2020 and 1st July 2021 to 31st July 2021. Similarly, the noise level also monitored during December 2019, January 2020 and February 2020 before imposition of the lockdown. During lockdown phase, the noise level had been accessed in the month of May 2020.

2.2 Monitoring sites

At 20 separate locations throughout the town, the acoustic level was measured. All these monitoring stations are divided into three sections such as commercial zone, residential and silence zone. Seven locations from both commercial and residential zones are selected and six stations were selected for silence zone. Some of these locations are belong to the commercial zone, such as Cinema square, Fandi square, Motiganj Bazar, Station square, ITI square, Padhuanpada square, and Policeline square, while others are in silence areas, such as Hospital gate, Durganurshing home, FM college, Zilla school, Near Kendriya Vidyalay (KV), and Police High School and others are in residential areas, such as Mandal bagicha, Near ACPL apartment, Khaparapada New Colony, Rajabagicha, Angargadia, Santikanana and Swastik tower.

2.3 Sampling and data acquisition

The sound level metre Model HD2110L was used to collect acoustic data at each of the 20 sample stations in and around Balasore town. The calibration of the equipment was carried out according to the manufacturer’s instructions. The measurements were conducted on working days at street level in and around the chosen locations’ major road connections. The instrument was comfortably set in road sides, with the microphone aimed at the source of noise. The equipment was placed 2 m distant from the reflecting object, and the data was gathered while standing 1.5 m above ground level on the roadside. Within 10–20 m gaps, noise levels were measured based on road width. Each station’s noise levels were measured in the morning (8–10 a.m.), afternoon (3 p.m.–5 p.m.), and evening (7 p.m.–9 p.m.). The noise levels were measured in four different directions at each station, and one reading was taken every 2 min, for a total of five readings within a 10-minute time frame [ 67 , 68 , 69 , 70 ]. All of the information is saved on a computer for further study.

For noise level data analysis, noise indices such as Lmin, Lmax, and Leq were calculated. The maximum, minimum, and equivalent noise levels were calculated using all of the recorded data on an excel sheet. The minimal sound pressure level is Lmin, the maximum sound pressure level is Lmax, and the equivalent continuous sound level during that time period is Leq. Again, L10 and L90 refer to sound intensities that are greater than 10% and 90%, respectively.

2.4 Community response

The community reaction was gathered through the use of questionnaires distributed to members of the public going along the various route segments. During the month of March 2020, the public’s replies were gathered and recorded on a computer. The questionnaire sent to the participants through whatsapp and in some cases hard copies are also shared and the process was completed during the month of November 2020. One hundred fifty participants have been responded to the questionnaire. This questionnaire was filled out by individuals (those who agreed) who were 18 years old or older. There were two sections to the questionnaire. The first section of the questionnaire is about demographics, while the second section is about various health issues related to the town’s acoustic noise. The questionnaire in this study was designed in accordance with Vianna et al. [ 71 ], and the questionnaire was constructed appropriately. A total of 150 people from various age groups replied to the questionnaire in this study. The first section contains demographic data such as name, gender, age, educational attainment, and marital status. After minor adjustments by Vianna et al. [ 71 ], the second half of the questionnaire was separated into the following sections. The respondents completed the noise sensitivity scale created by Weinstein [ 72 ] and Eysenc’s personality Inventory (EPI) in this study [ 73 ]. Two items given under perception of noise such as aware of noise pollution and environmental noise asked the participants to answer in 5-point Likert scale. The question based on annoyance level and anxiety are also in 5-point Likert scale. Questions are given on hearing condition, sound quality of the environment, personality traits such as aggression, depression, stability, working ability, tiredness and drowsy, sensitivity, relaxation, developing symptoms, and on health risk. This part asks about how people perceive noise from things like road traffic and other sources, and the answer is either Yes or No. High, Moderate, and Little annoyance in regard to noise sources; Noise exposure effects (hearing loss, sleep disturbances, headaches, fatigue, drowsiness, and other illnesses); Hearing condition (Excellent, Good, Moderate, and Poor); environmental sound quality (Normal, Moderate, and Noisy); and environmental perception (Yes, No, and Undecided) [ 9 , 71 , 73 ]. The Chi-square test in SPSS 20.0 was used to look into the correlations between demographic characteristics and annoyance, and other environmental factors and the ANNOVA test was used to look into the association between noise exposure and the probable impacts of that noise on this community. At a significance threshold of 0.05, the relationship between individual and combination socio-demographic characteristics was examined. The datasets were analysed using SPSS software (20.0).

3. Results and discussion

3.1 studies related to zone specific noise.

The average noise levels of the 20 stations of different categories have been accessed and presented in Table 1 (Before Lockdown), Table 2 (during lockdown) and Table 3 (Unlock phases). The data collected during the month December 2019 and January and February 2020 are considered as pre-lockdown phase. 17th March 2020 to 31st May 2020 considered as lockdown period. After 1st June 2020 it is considered as unlock phases or after lockdown period. The comparative monthly variation of equivalent noise levels of these areas having different land use type is presented in Figure 2 . The figure clearly depicts that there is a sharp trend of noise levels of the town during three phases of the lockdown. It also demonstrates that the noise level during the lock down phases is very low than unlock and before lockdown phases. The monthly noise variation of all the stations is depicted in the Figures 2 – 10 . In each figure, first three belongs to the monthly noise level before lockdown period, while the fourth one belongs to the lockdown period and the last portions belong to the unlock phases.

Noise levels in dB at different traffic squares of Balasore town during different time interval (pre-lock down phase).

Noise levels in dB at different traffic squares of Balasore town during different time interval (during lock down phase).

Noise levels in dB at different traffic squares of Balasore town during different time interval (post-lock down phase).

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the morning hour of commercial zone.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the afternoon hour of commercial zone.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the evening hour of commercial zone.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the morning hour of silence zone.

The Table 1 clearly depicts that the noise levels for commercial zone ranged from 57.7 to 91.6 dB, 57.3 to 91.6 dB and 56.8 to 93.7 dB for morning, afternoon and evening hour respectively. Similarly, the noise level for silence zone ranged from 57.4 to 90.3 dB; 58.8 to 91.7 dB and 53.5 to 91.6 dB during the morning, afternoon and evening hour respectively and from 55.9 to 85.6 dB; 56.8 to 89.8 dB and 50.2 to 91.6 dB during the morning, afternoon and evening hour respectively for residential zone. It can be summarised that the noise for all zones before lockdown period had a ranged from 55.9 to 91.6 dB; 56.8 to 91.7 dB and 50.2 to 93.7 dB during the morning, afternoon and evening hour respectively. Table 1 also clearly depicted that for all time the noise level ranged from 50.2 to 91.7 dB during before lock-down phase ( Table 1 ).

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the afternoon hour of silence zone.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the evening hour of silence zone.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the morning hour of residential zone.

Similarly, Table 2 clearly demonstrated that all zones lie in the range of 38.3 to 81.4 dB during lockdown period ( Table 2 ) and then the range gradually increased to 45.7 to 92.5 dB during unlock period ( Table 3 ). The equivalent noise levels of all zones lie in the range of 65.8 to 81.7 dB ( Table 1 ); reduced to 43.2 to 60.7 dB during lock-down period ( Table 2 ) and the range then gradually increased from 56.8 to 73.1 dB during unlock period ( Table 3 ). The permitted limit for the said locations, as defined by the CPCB for Indian road conditions, is 65 dB during the day and 55 dB at night [ 37 ]. During the day time, the noise level exceeded the permitted limit [ 74 , 75 , 76 , 77 , 78 ]. The noise level during unlock phase and before imposing lockdown was beyond the permissible limit in the present study. It was reported that, if the exposure of noise level is more than 80 dB (A), then risk of hypertension will increase [ 34 ]. More research is needed to investigate the effect of such noise level on the public’s health in future study.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the afternoon hour of residential zone.

Comparative equivalent noise level (first three are before lock-down, middle on during lock-down and the last twos are during unlock phase) for the evening hour of residential zone.

From the monthly variation it was demonstrated that the noise levels of residential areas during the morning hour are decreased by a noise level of 24.8 dB and then it increased up to 15.1 dB during unlock phase in Mandal Bagicha area. Similarly, the noise levels in other monitoring areas decreased by a noise level of 23.5, 23, 26.8, 23.3, 24.5 and 24 dB and then it was increased up to 14.7, 14, 15.5, 13, 14.7 and 19.95 dB for ACPL, Khaparapada, Rajabagicha, Angargadia, Santikanan and Swastik tower, respectively ( Table 1 ). During afternoon hour, the maximum reduction of noise level was noticed at Rajabagicha area (30.2 dB) and then it increased up to 17 dB during the unlock phase. From the Table 1 , it clearly depicts that maximum noise reduction between before lock-down phase and during unlock phase was observed at commercial zone (more than 25.5 dB) followed by residential zone (more than 25 dB) and silence zone (more than 22 dB). All these data are mentioned here are in an average data. Similarly, the maximum growing noise level between during lock-down and unlock phase was also noticed at commercial zone (more than 17.8 dB) and followed by silence zone (16.7 dB) and residential zone (14.1 dB). During evening hour and at Padhuanpada square maximum noise reduction i.e., 28.6 dB was noticed, while the lowest reduction was at 16.3 dB during morning hour at Durga Nursing home. Again, maximum increase of noise level was noticed at Cinema square (21.9 dB) during the evening hour, while the minimum increase noise was noticed at Hospital gate (8.7 dB) during the evening hour also.

Table 1 also clearly depicted that the equivalent noise level during before lock down phase ranged from 77.2 to 80.5 dB; 75.7 dB to 81.7 dB and 75.5 to 81.5 dB for morning, afternoon and evening hour respectively. But the noise level during the lock-down phase ranged from 53.9 to 56.2 dB; 52.8 to 54.4 dB and 51.1 to 53.4 dB during the morning, afternoon and evening hour respectively ( Table 2 ). Similarly, the noise level during the unlock phase ranged from 69.2 to 71.2 dB; 70.3 to 71.5 dB and 70.5 to 73.1 dB during the morning, afternoon and evening hour respectively ( Table 3 ). The noise level at silence zone ranged from 72.6 dB to 76.3 dB; 74 to 78.2 dB; 73.4 to 78.4 dB during before lock down phase; 51 to 58.3 dB; 49.6 to 56.7 dB and 50 to 60.7 dB during lock-down phases at morning, afternoon and evening hour and 65.7 to 72.9 dB; 66.9 to 72.7 dB and 68 to 69.5 dB during morning, afternoon and evening hour respectively. In the residential areas it ranged from 69.5 to 73.2 dB; 68.2 to 74.7 dB and 65.8 to 72.5 dB during before lock down phase; in lock-down phase the noise level ranged from 45.9 to 48.4 dB; 43.2 to 45.4 dB and 43.4 to 45.1 dB and in unlock phase it ranged from 60.5 to 61.9 dB; 57.3 to 61.5 dB and 56.8 to 58.5 dB in the morning, afternoon and evening hour respectively.

In location wise, Tables 1 – 3 clearly depicts the noise variation in all the monitoring stations. These Tables demonstrated that there is a reduction of 25.9 dB, 26.7 dB; 30.3 dB in three different monitoring hours for site 1 of commercial zone. Conversely, the reduction is almost 26, 26.8 and 27.2 dB for site 2, 23.4, 28.2, 26 dB for Site-3 and a similar trend was found in all other monitoring sites belong to commercial zone. In the commercial zone the minimum noise reduction ranged from 22.9 to 28.2 dB and 23.9 to 30.3 dB during afternoon and evening hour of the commercial zone. Again, the reduction of noise level ranged from 16.4 to 23.3 dB; 19.2 to 26.2 dB and 17.7 to 26.8 dB of silence zone and from 23 to 26.8 dB; 23.3 to 30.2 dB and 22.4 to 28.4 dB of residential zone during morning, afternoon and evening hour respectively. This result clearly depicted that there is almost same trend in the noise level reduction, both in commercial and residential zone of the town. The minimum noise level reduction was more than 15 dB and found at silence zone of the town and clearly depicted that due to the nationwide lock-down imposition, there was a sharp reduction in the noise level. It will impact the environment in a positive manner.

In comparison between Leq values of a particular sites during the lock-down period with unlock phase, there was sharp increase in the noise levels of each location. Noise levels from 13.9 to 17.7 dB was increased during the morning hour in between lockdown and unlock phases. Similarly, the noise levels increased by 17.1 to 18.1 dB and 19 to 21.9 dB in afternoon and evening hour of commercial zone. Again, the increased noise level ranged from 9.9 to 15.5 dB, 12.3 to 17.3 dB and 8.7 to 19 dB of silence zone and ranged from 13 to 15.5 dB, 13.3 to 17 dB and 13.3 to 13.6 dB of the residential zone during morning, afternoon and evening hour, respectively. Due to slight relaxation provided by the local administration, there was a sharp increase in noise level of the town. This trend was more commercial zone. In the present study it is also reported that there is no relation between the different monitoring hours and the situation i.e., before imposing lockdown and after imposing and lifting the lockdown phase of the town. But there is a good association between different areas such as residential, commercial and silence zone with unlock and before lock down phase of the town ( Table 4 ). In case of monthly noise level variation with different phases of the lockdown situation there is also good association between them and is presented in the Table 5 .

Two way ANNOVA analysis for equivalent noise levels during unlock and before lockdown phases with different areas.

R squared = 0.829 (Adjusted R squared = 0.823).

One way ANNOVA analysis for monthly equivalent noise levels with different areas.

In the present study, it was found that the noise level in the residential areas is growing on due to imposition of lockdown in the town. Due to lockdown, the commercial areas of the town and for such the people are selling different grocery items in the different parts of the residential areas. The open shops are instantly made on the roadside and there is slight gathering around such place. These shops are opened from 7 am to 7 pm during the unlock phase while it was opened from 7 am to 2 pm during the lockdown phase. Around the market or shop area there was gathering and due to which, the noise level during the unlock phase was raising. Again, during the unlock phase, the noise level suddenly increased due to immediate rush in different parts of the town, due to purchase of goods for their house. They creating a such situation unnecessarily by gathering around the temporary shops.

In case of silence zone, schools and hospitals were taken in the present study. All the monitoring stations were located along the main road. College and school squares are also along the road of different hospitals. Many private clinics and hospitals are also very close to the schools and colleges of the town. During lockdown, many shops, schools and colleges and other establishments were closed. All medicinal shops are opened throughout the day time. But vehicles are flowing on the road due to health matter. Continuous flowing of many vehicles including heavy vehicles on the road are controlled, but running of the two wheelers, ambulances and responsible for the noise levels of the town.

3.2 Community responses

During the month of March 2020, the public’s replies were gathered and recorded on a computer. The questionnaire was supplied to the participants both in online and offline mode. Those are expertise in the android mobile phones or in their PC or laptop they are responded to the questionnaire through online mode. Those are not comfortable in using these devices, asked the researcher to provide the such through offline mode and also provided to them as such. After getting their responses, it was then transferred in to MS Excel for its further analysis.

The questionnaire was completed by 150 people, as mentioned in the content and methods section. The average age of the responders was 37.8 years old, with a standard deviation of 9.4 years. Table 6 lists the various personal characteristics of the individuals. Table 6 clearly depicts that the majority of the participants are male respondent (59.3%), with 68.7% of the total completing their education at the graduation level. In the present study, majority of the participants are employed. Majority of the participants (78.7%) participated in this survey work are married. In the present study most of the young generation (48%) between the age of 18 to 30, responded to this questionnaire.

Personal characteristics of respondents (in percentage).

The Pearson Chi-square of noise discomfort to different demographic characters is shown in Table 7 . Table 7 clearly depicts that there is a good association between annoyance and gender of the present work. Again, there is no direct relationship between annoyance and other demographic characteristics, according to the data.

Relation between demographic character and annoyance.

In this study it was found that 36.7% individuals were extremely irritated, while 39.5% remain silent. In a study conducted by Alimohammadi et al. [ 73 ] on White-collar employees in Teharan, it was discovered that married people were more irritated than unmarried people. But in the present study it was contradicted that result ( p  = 0.217).

The participants’ perceptions on noise, health issues, hearing conditions, sound quality of the environment, environmental problems, opinion of participants on noise preventability, sensitivity to noise, annoyance, and the importance of controlling the town’s noise were all examined in the current study and presented in the Table 8 .

Participant’s perception towards different aspects of noise pollution.

On awareness towards road traffic noise pollution, majority of the participants (59.3%) were aware of it. More than 30% respondents were strongly aware about the noise pollution, which is also a good sign for the society. Regarding health issues majority respondents (36.7%) opined about a little impact of noise pollution on their health, while 24.6% respondents remain silent and only 18% viewed that they suffered moderately by the noise pollution. On hearing condition most of the participants (38%) were in moderate condition, while 30% responded as good in condition. Only 27.3% opined that their hearing condition was not so good or in bad condition. How much the hearing problem is affected is not studied in the present study. The researcher aimed to conduct the audiometry study of these respondents very soon to know their actual level of hearing in the next study. Noise induced hearing loss is also the most frequently recognised occupational disease in many countries [ 79 , 80 , 81 ].

The sound quality of the town was not so good as per the response of the participants. Due to such issues, they face a lot of problems (56.7%) in their day-to-day life. According to the findings, 40.7% of the participants suffered illness, while most of them faced headache (54.7%) due to road traffic noise. How much it affects the public health and what are the possible symptoms are developed is to be investigated in the next phase of study. Majority of the respondents (57.3%) responded that they annoyed often. Running of vehicles (89.3%) is the major source of pollution, followed by railway (76.7%), two wheelers (75%), honking (70.7%) ( Table 8 ).

The acoustic quality of the area was described as noisy by the majority of the participants (60%). According to the study, majority of the of interviewees felt that road traffic noise was polluting the environment. When the participants’ knowledge was assessed, most of them said that road traffic noise poses a significant health risk. Noise pollution upset 67.3% of the participants, while 58.7% were sensitive to noise and 60% found it difficult to relax in these situations. More than 48% felt depressed, 82% were felt tired, 48.7% were not working in a stability manner. It may be due to the effect of the noise pollution.

The chi-square test was used to determine the relationship between age and annoyance in this study, and no link was found at p  = 0.01. However, there is a strong association between annoyance and gender ( p  = 0.004). There was also a link between work place noise levels and annoyance, according to Allomohammadi et al. [ 73 ]. But this result is similar to the present study. It can be said that occupation is not a good characteristic towards annoyance. According to reports, there is no correlation between age, education, or marital status and the town’s level of annoyance. The current study’s findings are comparable to those of Ohrstrom et al. [ 82 ], who found that age, sex, and other characteristics do not explain differences in annoyance between people and is very similar to the results of the present study. However, it has been reported in many research that annoyance is the most vulnerable consequence of traffic noise exposure [ 83 , 84 ], which contradicts the findings of the current study in many circumstances.

There is good association between gender and drowsiness of the public ( p  = 0.015) ( Table 9 ). Table 9 also demonstrates that there is an association between drowsy and qualification. Table 10 depicts that there is an association between relaxation and gender ( p  = 0.001) and age ( p  = 0.006). Most of the demographic characters have a good association with noise sensitivity ( Table 11 ). Noise sensitivity has a good association with gender ( p  = 0.001), age ( p  = 0.005), marital status ( p  = 0.001) and qualification ( p  = 0.038) of the present study ( Table 11 ). Table 12 reveals that both gender ( p  = 0.001) and marital status ( p  = 0.001) has an association with anxiety of the noise pollution ( Table 12 ). Gender is not a significant element in the influence of noise concern, according to certain studies [ 5 , 85 ]. Similar results also depicted in the present study. There was also a link between the individuals’ age and sleep problems ( p  = 0.046). It was also said that age is not a significant factor when it comes to the effects of noise exposure [ 5 , 80 ]. Increased parent-reported sleep issues were identified in the few studies that looked at the link between noise and child/adolescent sleep [ 23 , 82 ]. Sleep fragmentation, sleep continuity, and total sleep time have all been linked to noise [ 24 , 25 ]. There was no association between sleep duration and hourly minimum noise levels [ 86 ]. Again, it was also reported that there was no relation between sleep efficiency and mean noise levels, according to Missildine et al. [ 87 ]. But, the result of the present study contradicts it and it shows that there is an association between sleep problems and noise level of the town ( p  = 0.016).

Relation between demographic character and drowsy.

Relation between demographic character and relax.

Relation between demographic character and sensitive.

Relation between demographic character and Anexiety.

Table 13 depicts the results of ANNOVA analysis between noise annoyance and demographic characteristics. The table clearly depicts that there is an association between annoyance and gender of the study. However, there is no statistically significant link between other demographic factors and annoyance. There is a link between sex and anxiety ( p  = 0.033) as seen in Table 14 . There is no direct relation between sensitivity with the demographic characters except marital status ( Table 15 ). Table 16 reveals that there is an association between relaxation and age ( p  = 0.008) and sex ( p  = 0.001) of the participants of the present study. Table 17 shows the relation between annoyance and different environmental issues. This table clearly depicts that there is a strong association between relaxation, sensitivity, environmental noise, anxiety, irritation. Different vehicles are running on the main road of the town. During lock-down and unlock phases, ambulances are flowing from different areas of the town to the district hospital centre and also to the other clinics of the town. it has been reported that noise sensitivity—internal states that increase the chance of noise annoyance [ 88 ]—could alter the relationship between noise and health. Noise sensitivity has been linked to the beginning of depressed and psychological symptoms in adulthood. Higher morning saliva cortisol levels were linked to significant noise irritation and residing in high-noise locations in adolescents [ 89 ]. We did not have a way to gauge noise sensitivity or annoyance, so we could not assess its impact [ 90 ].

Analysis of ANNOVA between demographic characteristics and annoyance.

R squared = 0.074 (Adjusted R squared = 0.041).

Analysis of ANNOVA between demographic characteristics and anxiety.

R squared = 0.061 (Adjusted R squared = 0.028).

Analysis of ANNOVA between demographic characteristics and sensitivity.

R squared = 0.128 (Adjusted R squared = 0.098).

Analysis of ANNOVA between demographic characteristics and relax.

R squared = 0.118 (Adjusted R squared = 0.087).

Analysis of ANNOVA between annoyance and environmental factors.

R squared = 0.508 (Adjusted R squared = 0.476).

The current research clearly shows that persons in the study locations are sensitive to noise levels based on their age. Respondents are employed in a variety of sub-urban work sites. They are subjected to various types of noise. They are irritated by the noise levels in the vicinity as a result of this. It is impossible to say that the level of noise in their workplace is the sole source of their annoyance, although it could be one of them.

During unlock phases, different offices are also opened in a regular and controlled manner. The running of vehicles on the road also growing accordingly and that may affect the public health in anyway. Different construction works also going on in many parts of the town and it may cause problem to the public of the town. Heavy vehicles carrying various raw materials are also moving on this road due to road building in various portions of the road. Vehicles are driven at all hours of the day and night. People of all ages are directly exposed to these levels of noise. This activity may exacerbate their sleeping problems.

4. Conclusion

Our findings may have been influenced by the fact that the noise level decreased due to the imposition of the nationwide lockdown and it then increase sharply due to the incoming of unlock phases. Still, the reported noise level of the town was beyond the permissible limit except lockdown phases in residential and silence zone. It was reported in the present study that there is a good association between different areas such as residential, commercial and silence zone with unlock and before lock down phase of the town. In case of monthly noise level variation with different phases of the lockdown situation there is also good association between them and is presented in the Table 5 . Finally, studies have demonstrated that the relationship between noise and health differs depending on sex, health status, and other factors but we lacked the sample size to evaluate the relationship by subgroup. Longitudinal designs, enhanced exposure assessment, and objective sleep assessments of whether particular subgroups of teenagers are more susceptible to the potential negative effects of environmental noise, should be prioritised in future investigations. Direct regulation of noise sources as well as changes to the built environment are two public health techniques for reducing noise exposure [ 21 , 91 ]. We were unable to demonstrate a temporal relationship between exposure and outcome since the study was cross-sectional. Future research may want to utilise objective of audiometry test to test the exactness of the hearing quality of the respondents of the town.

Acknowledgments

The authors are very much thankful to Indrajit Patra and Pravat Kumar Mandal for their support in monitoring the noise levels.

Conflicts of interest

The authors declare that they have no conflicts of interest with regard to the content of this report.

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Sound Pollution issues and mitigate measure, Case Study : Taman melati, Gombak, KL

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Impacts of noise pollution from high-speed rail and road on bird diversity: a case study in a protected area of Italy

• Research Article
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• Published: 20 April 2024

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• Ester Bergamini 1 , 2   na1 ,
• Sofia Prandelli   ORCID: orcid.org/0009-0007-0922-5790 2   na1 ,
• Fausto Minelli 3 &
• Roberto Cazzolla Gatti 2 , 4  

The disturbance of infrastructures may affect biological communities that are exposed to them. This study assesses the impact of high-speed (highway and railway) infrastructures in a protected study site, the Natural Reserve Fontanili di Corte Valle Re (Emilia–Romagna, Italy). We compared bird diversity with sound intensity and frequency in three sampling areas, increasingly distant from the infrastructures at the border with the reserve, during the last 4 years (2019–2022), monitoring sedentary, nesting, and migratory bird species. We hypothesize a decreasing diversity closer to the source of disturbance, which is mostly attributable to noise pollution. Our findings confirmed this trend, and we show that, in particular, disturbance seems to influence species richness more than the total abundance of birds. We also discovered that highway disturbance was much higher than railway in terms of frequency and duration. In light of these results, we suggest that some species, which have a behavioral ecology strongly based on singing to communicate with each other for their reproductive and defensive strategies, may suffer more from constant acoustic disturbance. The installation of effective noise barriers to shield the sound produced by the highways should be considered a mandatory request not only in proximity to houses but also in the vicinity of protected areas.

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Introduction

Anthropogenic disturbance has been widely studied in ecology since its effects have consequences on communities and their composition (Ausprey et al. 2023 ). According to Pickett et al. ( 1989 ), disturbance can be defined as a change in the ecosystem caused by an external factor to the level of interest. Another well-accepted idea is that disturbance, as every process that causes loss of biomass in a community (Grime 1977 ), also has a negative impact on a community and its elements.

Previous studies showed that the proximity to disturbing infrastructures is one of the biggest causes of biodiversity loss (Van Der Zande et al. 1980 ). In particular, the number of negative effects of roads and railways is high when considering mortality due to vehicle collisions, particularly for reptiles, amphibians, and mammals. Although birds showed contrasting effects on infrastructure’s presence, the impact of the acoustic disturbance may be relevant for these taxa, even if poorly investigated. A recent study from Ausprey et al. shows how any kind of disturbance, in agricultural landscapes, leads to a decline in species and that sensitivities to anthropogenic disturbance are species-specific (Ausprey et al. 2023 ). The decrease in abundance and species diversity in birds is particularly documented at short distances, up to 1 km from the source of disturbance (Benítez-López et al. 2010 ). The disturbance from viable infrastructures is mostly acoustic and its consequences are proportional to the magnitude of the noise. There is preliminary evidence that birds are less affected by train passage, which is discontinuous than by the motor vehicles on the highways, which is quite constant (Wiącek et al. 2015 ). Species that possess communicative skills and base their reproductive behaviors mostly on vocalization are certainly the most affected (Lucas et al. 2017 ). A study conducted by Reijnen and Foppen ( 2006 ) showed that an important level of disturbance, such as big and busy roads, is the main cause of negative abundance trends of birds, compared to the presence of the infrastructure itself.

At the same time, there might be a positive effect that increases bird diversity due to the landscape’s heterogeneity created by roads and railways (Morelli et al. 2014 ; Kajazer-Bonk et al. 2019 ). Close to the infrastructure, woody habitats would be side by side with crops, leading to an increase in the amount of food availability. Moreover, the traffic could lead to a reduction in the number of predators, while artificial light would extend diurnal activities in winter. Having different habitats also means having more nesting sites and chances of hiding (Kajzer-Bonk et al. 2019 ).

This study aims to analyze the impact of acoustic disturbance produced by high-speed road and rail on bird diversity of migratory, nesting, and sedentary species of a protected area in northern Italy. We hypothesize that both species abundance and richness increase with incremental distance from the source of disturbance. On the other hand, we evaluated how the mid-domain effect could lead to a higher abundance and diversity in the core of the reserve and a decrease of them at the edge (Colwell and Lees 2000 ).

Materials and methods

The study was conducted in the bird-ringing site of Natural Reserve Fontanili di Corte Valle Re, in Italy. The site (coordinates 44.7672 N, 10.5328 E) has an area of 37 hectares and is located in the municipality of Campegine (Reggio Emilia). Data were collected at an increasing distance from two big infrastructures: the A1 highway and the high-speed railway Milano–Bologna, both adjacent to the protected area. The presence of specimens was studied for the reproductive and migratory seasons, from autumn 2019 to autumn 2022. The monitoring was done for the MonITRing Project of the National Centre of Ringing (CNI), of the Superior Institute for Environmental Protection and Research (ISPRA).

The protected area is one of the last flatland springs remaining in its natural state. Around the regional Reserve, water crosses cultivated fields and, near the springs, it leads to the growth of hydrophilic plants and reeds. The woods in which nets were located is mainly composed of black alder ( Alnus glutinosa ), grey sallow ( Salix cinerea ), alder buckthorn ( Rhamnus frangula ), black elderberry ( Sambucus nigra ), field elm ( Ulmus minor ), blackthorn ( Prunus spinosa ), English hawthorn ( Crataegus laevigata ), and dogwood ( Cornus sanguinea ). Different microhabitats allow the presence of a rich and varied fauna (Parchi Emilia Centrale 2022 ). The vulnerability of the Reserve, besides the rarity of its flatlands, is due to the closeness to the A1 highway, one of the busiest in Italy, and the adjacent high-speed railroad. The area is also part of the EU Natura 2000 network (Mézard et al., 2009 ) within the Area of ecological restoration Fontanili Media Pianura Reggiana and it is a Site of Community Importance (SCI), in which habitats are protected (Ambiente, Regione Emilia Romagna 2022 ).

Sampling methods and data analysis

The catch of the specimens took place using mist nets that have a mesh size of 16 mm, height of 2.5 m, and width of 12 m. Four of them were placed in three spots hereafter denominated Near, Intermediate, and Far, for a total net length of 48 m in each of them. The three transects were all placed perpendicular to the viable infrastructures and in areas where plant cover and composition are mostly the same.

Highways and railways can be considered the main sources of disturbance since the Reserve has few visitors per year and the trails are far from the nets. The seasonal presence of hunters in the surrounding areas may be considered an additional disturbance factor for the birds and may push them into the Reserve’s core. Distance from the Reserve and high-speed ways was 160 m from the nearest net (Near), 320 m from the intermediate one (Intermediate), and 425 m from the farthest one (Far) (Fig. 1 ). To ensure comparability, we checked that the three areas, although different in shape, have similar vegetation and are surrounded by the same type of agricultural field. One main difference among the three sampling sites is that the Near site is surrounded by a slightly higher forest cover, in an L shape, than the other two sites. We also confirmed that the three sampling points were located in areas with similar vegetation and environmental conditions.

Map of the study site, the regional Natural Reserve Fontanili di Corte Valle Re, with the indication of the three sampling points in which the mist nets were located and the high-speed ways

Acoustic disturbance has been measured in the center of three transects using professional digital phonometers with a range of measures from 30 to 130 dBA and a sensitivity of 0.1 dBA, during optimal weather conditions, without wind or adverse meteorological conditions. The phonometers were set in the center of the three transects, detecting values at the same time for periods of 30 min and three repetitions during the day. We measured the acoustic disturbance in randomly selected days to provide empirical evidence of the differential acoustic impacts in the three sampling areas. We assumed that the acoustic disturbance throughout the year is similar to the average noise detected during the randomly selected days of recordings. We have good reasons to believe that our assumption is correct because the only variable factor is the wind and it is quite unpredictable during the seasons, while the railway and highway traffic noise remains almost constant throughout the year. The measurements returned 3573 records — two measurements every second — for every point, for a total of 10,719. To separate noise pollution caused respectively by railway and highway infrastructure, data were separated by calculating, for each study point, the value corresponding to the 95th percentile, dividing them into average noise values and peak noise values.

Bird captures were made using the standard procedure for birds’ ringing. The nets were opened before sunrise and monitored six times in the following hours. Ancillary data were collected including time of the catch, ring code, recapture, species name, Euring specific code, status, molt, plumage, weight, age, sex, fat, muscle, measurements of tarsus, chord, and third remiges’ length. The equipment included a bird identification guide, rings of various sizes, banding pliers, different rules, and a portable scale. Data has then been transferred to electronic datasets.

The statistical analysis, performed with the software R and ggplot package (R Core Team 2016 ), included the calculation of the AED index ( Absolute Effective Diversity ), to estimate the number of species observed in an area, including those not detected (Cazzolla Gatti et al. 2020 ). We also compared temporal trends, during years and seasons, between the three areas. To understand whether the acoustic disturbance affects species diversity and abundance Wilcoxon’s test (Wilcoxon 1992 ) was applied.

In the three sampling nets, 41 different species of birds were captured and ringed, and their relative abundance was recorded (Table 1 ). The three sampling sites showed differences in their richness and abundance, with higher values always for the Far net (Table 2 ). Some of the species protected under the Bird Directive 2009/147/CE have been ringed and collected in this study: the marsh warbler ( Acrocephalus palustris ), the pied flycatcher ( Ficedula hypoleuca) , the red-backed shrike ( Lanius collurio ), the nightingale ( Luscinia megarhynchos ), and the song thrush ( Turdus philomelos ).

To better analyze the contribution of resident and migratory species to the total richness and abundance in the three sampling areas, we separate species collected in Spring from those collected in Autumn (Figure 2 ). In terms of species richness, the Far net shows higher values for both periods ( p = 0.021 between Near and Far sampling points), whereas Spring abundance shows lower values in the Far net compared to the other sampling sites ( p = 0.036).

Bird species richness (S) and total abundance (N) in the whole study period (a and d, respectively), in Spring (b and e), and Autumn (c and f). The median (central line in the box) represents the values that fall between the second (lower quartile value) and the third quartile (upper quartile value). The whiskers include data that lie between the 10th percentile (lower bound) and the lower quartile value, and between the upper quartile and the 90th percentile. Points outside the lower and upper bounds are outliers

Time series of noise pollution recordings show a clear separation of the three sampling nets, with higher values (in dB) at the Near sampling point (Figure 3 ). Then, the time series were separated into peak noise values and average noise values. This separation of noise pollution allowed us to clearly show that the disturbance caused by the passage of high-speed trains (Fig. 3 b) is scattered (because each recorded peak corresponded to a monitored time of train arrival), whereas the disturbance caused by the noise of motor vehicles on the highway is constant (Fig. 3 c). In both cases, the Near sampling point recorded the highest noise pollution, which was higher than at the Intermediate and Far nets both for railways and highways (Fig. 4 ).

Time series of acoustic disturbances (in dB) ( a ) separated as peaks noise values ( b ) and average noise values ( c ). To separate the noise pollution caused respectively by railway and highway infrastructure, acoustic recordings were separated by calculating, for each sampling point, the value corresponding to the 95th percentile, dividing them into average noise values and peak noise values

Noise pollution (in dB) distribution ( a ) separated into peak values distribution ( b ) and average values distribution ( c ). The median (central line in the box) represents the values that fall between the second (lower quartile value) and the third quartile (upper quartile value). The whiskers include data that lie between the 10th percentile (lower bound) and the lower quartile value, and between the upper quartile and 90th percentile. Points outside the lower and upper bounds are outliers

We analyzed the impact of a highway and a high-speed railway on the species diversity of a protected area in Italy, from autumn 2019 to autumn 2022.

Species richness decreases in the proximity of the sources of disturbance. In fact, bird diversity near the infrastructures is lower than the one observed in the more distant point, as confirmed also by previous studies: bird species richness is strongly affected by human disturbance such as agriculture, forest harvesting, roads, and urban and industrial areas in the surroundings of a habitat (Zhang et al. 2013 ). The significant differences between the nearest and farthest sampling points confirm our hypothesis of a higher impact due to high-speed ways, although the intermediate sampling net shows contrasting results attributable to the mid-domain effect that may lead to a higher abundance and diversity in the core of a reserve and a decrease of them at its edge (Colwell and Lees 2000 ).

In our study, bird abundance was significantly higher in the central area compared to the sampling point near the disturbance source. This is probably due to the mid-domain and edge effects, which lead the specimens to concentrate at the core of the Reserve, seeking protection in a less disturbed habitat. Bird diversity in the center of the Reserve was even a bit higher than at the farthest sampling point from noise pollution, and this may be because this point is close to the limit of the protected area and to the agricultural fields in which hunting seasonally takes place.

Total abundance shows a significant growing trend moving away from the source of disturbance, confirming the hypothesis that infrastructures represent the major reason for differences in bird species. Although a general increase is evident, it is not always linear and may reflect the different distribution of species within the reserve and their different behaviors. Birds that vocalize more could live further away from the source of noise pollution, which would interfere with the correct communication of individuals and consequently with their reproductive strategies, often based on an elaborate execution of the song, as already confirmed by different studies: with increasing background noise levels, males of European robin proved to be more likely to move away from the noise source and changed their singing behavior gradually (McLaughlin and Kunc 2013 ), and the number of birds per study area was shown to increase with the distance from the roads (Polak et al. 2013 ). Generally, highway noise has an impact on birds within several hundred meters (up to 1 km) from the source, despite visual disturbance and vehicular pollutants extended for a shorter distance from highways (Dooling and Popper 2016 ; Benítez-López A. et al. 2010 ).

In our sampling sites, we found a significantly higher bird abundance during autumn than spring and this may be due to migratory species that are probably less affected by anthropic noise while sedentary species are the most impacted. Anthropogenic noise pollution has been observed in other studies to play stronger effects on breeding birds than, in opposition to our results, wintering species, assuming these different responses may reflect species differences in acoustic communications (Wang et al. 2013 ; Catchpole et al. 2003 ). Breeding birds often need an elevated number of frequencies and types of acoustic contacts to complete the entire breeding cycle, such as mate attraction, territorial advertisement, or parent-offspring communication (Wang et al. 2013 ).

The absolute and effective diversity index (AED), which provides a comparable estimation of species missed from the sampling, confirms an important increase in the number of species moving away from high-speed ways. Some of these species could have different habitat preferences, while others, probably present in the reserve, have never been captured for random reasons. The index provided a value of potentially 50.81 living in the Reserve, which seems reliable as many species have been identified besides the 41 species detected in this study. The continuation of monitoring will certainly improve this work, allowing a higher bird species detection.

The highway A1 Milan–Naples and high-speed railway Milan–Bologna are highly busy causing a strong acoustic disturbance as measured by our phonometers. This may also be the reason why the reserve is rarely visited by people, as nature appreciation is enhanced by natural sounds and decreased by extraneous noises produced by road traffic, for instance (Chau et al. 2010 ).

Noise peaks in correspondence with the scattered passage of high-speed and regional trains seem to be less impacting for bird communication than the constant noise produced by the highway although both may importantly contribute to the acoustic disturbance.

It has been documented how the background acoustic disturbance — which grows exponentially in combination with the transit of high-speed trains or with the use of car horns — has repercussions on birdlife (Pickett et al. 1989 ; Parris and Schneider 2009 ; Lucas et al. 2017 ).

Reijnen et al. ( 1995 ) showed evidence that, in woodland, noise is probably the most critical factor in causing reduced densities close to roads. In regression analysis, using vehicle noise and visibility as response variables, the noise seemed to be the best and, in many species, the only predictor of observed depressed densities in the proximity of the road. Similarly, in open agricultural fields, several species of breeding birds showed a density reduction of almost 100% due to dense traffic, possibly causing an important loss of species richness (Reijnen et al. 1997 ), with total population density reduced by 39% in open agricultural grasslands and 35% in woodlands. Several studies also on non-bird species support the finding that, generally, animals change their distributions in response to anthropogenic noise, as the observation of Sonoran pronghorn’s behavior in avoiding loud areas due to military jet overflights (Barber et al. 2009 ). High levels of noise have been shown to affect wildlife physiological aspects, including temporary and permanent hearing loss (Barber et al. 2009 ).

In light of our findings and previous studies, to better protect birdlife and wildlife in general, it would be important to limit the extent of the disturbance by setting anti-noise barriers alongside the infrastructures. Most of the scientific literature is in line in acknowledging that anti-noise walls can reduce acoustic pollution of 5-15 dB: the volume of the sound pressure which a wall can absorb is directly proportional to the size of the sound pressure of the incoming source, considering that the decibel scale is logarithmic, even a small numeric variations translate into a major changes in sound perception (Hranický et al. 2016 ). According to Adamec et al. ( 2011 ), on average, well-designed barriers reduce noise by approximately 4 or more dB, depending on the geometry of traffic noise propagation.

Different types of noise barriers can be considered a valid help: reflecting walls with a smooth surface or absorbing walls with rugged folds are useful not only for the reflection of sound waves but also for their direct limitation; however, it is important to note that reflective barriers are often made with transparent materials and may be a danger for birds if not appropriate visual deterrent is placed (Hranický et al. 2016 ). Another related issue can occur where noise barriers are built only on one side of the track and animals can remain trapped on the infrastructure, but a simple solution can be the placement of stickers with dark contours of predatory birds for deterrence and further the integration of these structures with elevated ecological corridors (Hranický et al. 2016 ). In this specific case, noise barriers should reach a maximum height equivalent to the height of the tree crowns, as they could otherwise create an additional obstacle to the passage of moving birds.

Overall, our study was conducted in a relatively longer timespan (4 years) than most of the previous studies (Reijen et al. 2006 ; Wiacek et al. 2015 ) and, therefore, provides reliable evidence that road and rail traffic, particularly on high-speed ways, is one of the main causes of the loss of bird diversity, even in protected areas.

Data Availability

The data that support the findings of this study are available from the corresponding author, SP, upon reasonable request.

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Ester Bergamini and Sofia Prandelli equally contributed and shared the first authorship.

Authors and Affiliations

Department of Biology, University of Pisa, Pisa, Italy

Ester Bergamini

Department of Biological, Geological, BIOME-Biodiversity and Macroecology Lab, and Environmental Sciences (BiGeA), University of Bologna, Bologna, Italy

Ester Bergamini, Sofia Prandelli & Roberto Cazzolla Gatti

Ente di Gestione per i Parchi e la Biodiversità-Emilia Centrale, Modena, Italy

Fausto Minelli

Biological, Geological and Environmental Sciences Department (BiGeA), BIOME Lab, University of Bologna, Bologna, Italy

Roberto Cazzolla Gatti

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All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Ester Bergamini, Sofia Prandelli, Fausto Minelli, and Roberto Cazzolla Gatti. The first draft of the manuscript was written by Ester Bergamini with the supervision of Roberto Cazzolla Gatti, and all authors worked on manuscript revision and finalization with the lead of Sofia Prandelli. All authors read and approved the final manuscript.

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Correspondence to Sofia Prandelli .

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We certify that the manuscript titled “Impacts of noise pollution from high-speed rail and road on bird diversity: a case study in a protected area of Italy” has been entirely our original work except otherwise indicated, and it does not infringe the copyright of any third party. Its submission to Environmental Science and Pollution Research implies that it has not been published previously, that it is not under consideration for publication elsewhere, that its publication is approved by all authors, and that, if accepted, will not be published elsewhere in the same form, in English or any other language, without the written consent of the Publisher. The research activities have been conducted in collaboration with the Natural Reserve Fontanili di Corte Valle Re, which received authorization from ISPRA (Italian Superior Institute for Environmental Protection and Research) to capture and monitor birds (Determinazione di Servizio n. 7307 of 17/05/2018 (2018-2020) and 5720 of 01/04/2021 (2021-2023).

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Bergamini, E., Prandelli, S., Minelli, F. et al. Impacts of noise pollution from high-speed rail and road on bird diversity: a case study in a protected area of Italy. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-33372-0

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Received : 20 June 2023

Accepted : 13 April 2024

Published : 20 April 2024

DOI : https://doi.org/10.1007/s11356-024-33372-0

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