Skip to main content
SpringerLink
Log in

Linear regression model for noise pollution over central Delhi to highlight the alarming threat for the environment

  • Original Article
  • Published:
Modeling Earth Systems and Environment Aims and scope Submit manuscript

Abstract

Noise pollution is the most ignored and underappreciated problem in the world. Even though scientists all over the world have done a lot of research on noise mapping and possible solutions, these solutions are still a long way from being put into practice. Noise reduction is an important step toward making a community that can last for a long time. Without systematic noise mapping, it is hard to figure out how noise changes in space and time. Using the Norsonic sound level meter, this research provides a novel methodological framework to integrate linear regression models with acoustic propagation for dynamic noise maps in Central Delhi. The 17 most sensitive receptors are also located in the study area. The noise mapping has been performed with the help of Dhwani pro and Arc-GIS software. The results from the noise mapping shows that the study area has noise at hazardous level. The second order linear regression noise prediction model has also been used for prediction of noise levels with taking parameters vehicle flow, % of heavy motor vehicle and light motor vehicle as inputs. The prediction performance is ascertained using the statistical test. The predicted noise values show good correlation with the observed noise levels i.e., R of 0.90. The isolation barriers of 5 m height are also introduced in the noise mapping analysis using Dhwani pro. These barriers represent substantial improvement in the noise level. The overall scenario of noise pollution in the study area is at alarming level and requires immediate planning to control the situation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Ahamed R, Khan AM, Ahmed T (2019) Application of regression models to assess bus interior noise in Dhaka City. Int J Environ Stud 76(6):940–952

    Article  Google Scholar 

  • Alam W (2011) GIS based assessment of noise pollution in Guwahati city of Assam, India. Int J Environ Sci 2(2):743–751

    Google Scholar 

  • Allu SK, Srinivasan S, Maddala RK, Reddy A, Anupoju GR (2020) Seasonal ground level ozone prediction using multiple linear regression (MLR) model. Model Earth Syst Environ 6(4):1981–1989

    Article  Google Scholar 

  • Baffoe PE, Duker AA, Senkyire-Kwarteng EV (2022) Assessment of health impacts of noise pollution in the Tarkwa Mining Community of Ghana using noise mapping techniques. Global Health J 6(1):19–29. https://doi.org/10.1016/j.glohj.2022.01.005

    Article  Google Scholar 

  • Banerjee D, Chakraborty SK, Bhattacharyya S, Gangopadhyay A (2008) Modeling of road traffic noise in the industrial town of Asansol, India. Transp Res Part D: Transp Environ 13(8):539–541

    Article  Google Scholar 

  • Berglund B, Lindvall T, Schwela DH, World Health Organization (1999) Guidelines for community noise. World Health Organization. https://apps.who.int/iris/handle/10665/66217

  • Census India Report (2011) Census of India 2011 provisional population totals. Office of the Registrar General and Census Commissioner, New Delhi. https://censusindia.gov.in/nada/index.php/catalog/1428

  • Chand P (2018) Environmental protection and regulations in India: role of the Central Pollution Control Board. Indian J Public Adm 64(4):645–663

    Google Scholar 

  • Cirianni F, Leonardi G (2012) Environmental modeling for traffic noise in urban area. Am J Environ Sci 8(4):345–351. https://thescipub.com/pdf/ajessp.2012.345.351.pdf

    Article  Google Scholar 

  • CPCB (2015) Protocol for ambient level noise monitoring. Central Pollution Control Board, New Delhi. http://mahenvis.nic.in/Pdf/Report/report_epm_Noise%20Monitoring.pdf

    Google Scholar 

  • Eason SA(2013) Strategic noise mapping with GIS for the Universitat Jaume I Smart Campus: best methodology practices (Doctoral dissertation). https://run.unl.pt/bitstream/10362/9194/1/TGEO0102.pdf

  • Farcaş F, Sivertunb à (2010) Road traffic noise: GIS tools for noise mapping and a case study for Skåne region, vol 34. Citeseer, Sweden, pp 1–10

    Google Scholar 

  • Garg N, Sharma MK, Parmar KS, Soni K, Singh RK, Maji S (2016) Comparison of ARIMA and ANN approaches in time-series predictions of traffic noise. Noise Control Eng J 64(4):522–531. https://doi.org/10.3397/1/376398

    Article  Google Scholar 

  • Joshi N, Joshi A (2015) Role of urban trees in amelioration of temperatures. Int J Res Stud Biosci 3:132–137

    Google Scholar 

  • Kadam AK, Wagh VM, Muley AA, Umrikar BN, Sankhua RN (2019) Prediction of water quality index using artificial neural network and multiple linear regression modelling approach in Shivganga River basin, India. Model Earth Syst Environ 5(3):951–962

    Article  Google Scholar 

  • Kalaiselvi R, Ramachandraiah A(2010) August. Environmental noise mapping study for heterogeneous traffic conditions. In Proceedings of 20th international congress on acoustics, ICA:23–27

  • Kalawapudi K, Singh T, Dey J, Vijay R, Kumar R (2020) Noise pollution in Mumbai Metropolitan Region (MMR): an emerging environmental threat. Environ Monit Assess 192(2):1–20

    Article  Google Scholar 

  • Khan J, Ketzel M, Kakosimos K, Sørensen M, Jensen SS (2018) Road traffic air and noise pollution exposure assessment–a review of tools and techniques. Sci Total Environ 634:661–676

    Article  Google Scholar 

  • Kim P, Ryu H, Jeon JJ, Chang SI (2021) Statistical road-traffic noise mapping based on elementary urban forms in two cities of South Korea. Sustainability 13(4):2365. https://doi.org/10.3390/su13042365

    Article  Google Scholar 

  • Konbattulwar V, Velaga NR, Jain S, Sharmila RB (2016) Development of in-vehicle noise prediction models for Mumbai Metropolitan Region, India. J Traffic Transp Eng (Eng Ed) 3(4):380–387

    Google Scholar 

  • Kumar K, Jain VK (1994) A study of noise in various modes of transport in Delhi. Appl Acoust 43(1):57–65

    Article  Google Scholar 

  • Kumar K, Katiyar VK, Parida M, Rawat K (2011) Mathematical modeling of road traffic noise prediction. Int J Appl Math Mech 7(4):21–28

    Google Scholar 

  • Lesieur A, Mallet V, Aumond P, Can A (2021) Data assimilation for urban noise mapping with a meta-model. Appl Acoust 178:107938. https://doi.org/10.1016/j.apacoust.2021.107938

    Article  Google Scholar 

  • Nandakumar R, Chintalapudi KK, Padmanabhan V, Venkatesan R (2013) Dhwani: secure peer-to-peer acoustic NFC. ACM SIGCOMM Comput Commun Rev 43(4):63–74

    Article  Google Scholar 

  • Rao PR, Rao MS (1991) Prediction of LA10T traffic noise levels in the city of Visakhapatnam, India. Appl Acoust 34(2):101–110

    Article  Google Scholar 

  • Sampath S, Das SM, Kumar VS (2004) Ambient noise levels in major cities in Kerala. J Indian Geophys Union 8(4):293–298

    Google Scholar 

  • Swain BK, Goswami S (2013) Integration and comparison of assessment and modeling of road traffic noise in Baripada town, India. Int J Energy Environ 4(2):303–310

    Google Scholar 

  • Tang JH, Lin BC, Hwang JS, Chen LJ, Wu BS, Jian HL, Lee YT, Chan TC (2022) Dynamic modeling for noise mapping in urban areas. Environ Impact Assess Rev 97:106864. https://doi.org/10.1016/j.eiar.2022.106864

    Article  Google Scholar 

  • Teff-Seker Y, Berger-Tal O, Lehnardt Y, Teschner N (2022) Noise pollution from wind turbines and its effects on wildlife: a cross-national analysis of current policies and planning regulations. Renew Sustain Energy Rev 168:112801. https://doi.org/10.1016/j.rser.2022.112801

    Article  Google Scholar 

  • Van Renterghem T, Dekoninck L, Botteldooren D (2020) Multi-stage sound planning methodology for urban redevelopment. Sustain Cities Soc 62:102362. https://doi.org/10.1016/j.scs.2020.102362

    Article  Google Scholar 

  • Yang W, Cai M, Luo P (2020) The calculation of road traffic noise spectrum based on the noise spectral characteristics of single vehicles. Appl Acoust 160:107128. https://doi.org/10.1016/j.apacoust.2019.107128

    Article  Google Scholar 

  • Yirga SA (2019) Modelling reference evapotranspiration for Megecha catchment by multiple linear regression. Model Earth Syst Environ 5(2):471–477

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. CSIR-National Physical Laboratory, Dr. KS Krishnan Marg, New Delhi, India

    Adwaita Dwivedi, Priyanka Singh, Parag Chourey, Rohan Kamra & Mahavir Singh

  2. CSIR-Advanced Materials and Process Research, Bhopal, Madhya Pradesh, India

    Nishant Kumar & Kirti Soni

  3. Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India

    Priyanka Singh, Kirti Soni & Mahavir Singh

Authors
  1. Adwaita Dwivedi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nishant Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Priyanka Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Parag Chourey
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rohan Kamra
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kirti Soni
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mahavir Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kirti Soni.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 20 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dwivedi, A., Kumar, N., Singh, P. et al. Linear regression model for noise pollution over central Delhi to highlight the alarming threat for the environment. Model. Earth Syst. Environ. 9, 1909–1921 (2023). https://doi.org/10.1007/s40808-022-01594-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40808-022-01594-1

Keywords

Search

Navigation