Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Environmental noise prediction

This algorithm is a calculation programme for determining noise levels from road traffic, railways and industry.

Last change on 5th of January 2024, at 14:35 (CET) | Publication Standard 1.0
Publication category
Impactful algorithms
Impact assessment
Field not filled in.
Status
In use

General information

Theme

Space and Infrastructure

Begin date

1999

Contact information

opendata@groningen.nl

Link to publication website

https://gemeente.groningen.nl/geluidkaarten-voor-omgevingslawaai-inzien

Link to source registration

https://data.groningen.nl/dataset/algoritmeregister-gemeente-groningen

Responsible use

Goal and impact

The algorithm has been developed to make forecasts for policy-making and licensing purposes, among others. In the latter, the mathematical model is used to assess how much noise the project for which the permit is being requested will produce.

For instance, every 5 years, large municipalities make noise maps (also called 'noise maps') and an action plan to tackle environmental noise. These include noise from traffic, railways and industry. The maps show the noise levels within the municipality of Groningen due to road traffic, rail traffic and industrial sites in the year 2021. They also show how many residential residents are exposed to and affected by noise.

Considerations

The computational rules related to calculating and predicting environmental noise are extensive and complex. A computer can do this faster and more reliably than a human.

Human intervention

Basically, there is no human interference in the calculation itself. What is done with the forecasts afterwards is human work, though.

Risk management

Much research is done by various consultancies to determine the extent to which the calculated results correspond to reality.

Legal basis

The legal basis for this algorithm lies in several pieces of legislation. First, in the Noise Pollution Act. This law provides noise-sensitive functions (such as houses) with protection against noise pollution from road traffic noise, railway noise and industrial noise. In addition, the Environmental Management Act. The Environmental Management Act was the main environmental law until the Environment Act came into force on 1 January 2024. This act broadly lays down the legal means to protect the environment and the principles that govern it. From 2024, the Environmental Management Act will largely merge into the Environment Act. The Environment Act deals with the space in which people live, work and relax. This new law merges old laws and contains rules for what can be seen, smelled and heard outside.

Every five years, municipalities draw up a noise map and an action plan. This obligation stems from the European Environmental Noise Directive and is implemented in Dutch legislation. The environmental noise directive aims to avoid, prevent or reduce harmful effects of environmental noise.

Links to legal bases

  • Wet geluidhinder: https://wetten.overheid.nl/BWBR0003227
  • Wet milieubeheer: https://wetten.overheid.nl/BWBR0003245
  • EU-richtlijn Omgevingslawaai: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2002:189:0012:0025:NL:PDF
  • Omgevingswet: https://wetten.overheid.nl/BWBR0037885

Operations

Data

Noise Calculation and Measuring Regulations 2012, Manual on Measuring and Counting Industrial Noise (HMRI), Cnossos

Links to data sources

  • Reken- en meetvoorschrift geluid 2012: https://wetten.overheid.nl/BWBR0031722
  • Handleiding Meten en Reken Industrielawaai (HMRI): file:///H:/Mijn%20Documenten/Mijn%20Downloads/handleiding-meten-en-rekenen-inustrielawaai_internetversie_2004.pdf
  • Cnossos : https://circabc.europa.eu/sd/a/ebfc8895-79fd-44db-8782-c5b26f6b1e37/CNOSSOS-

Technical design

The algorithm follows a European and nationally established set of computational rules to arrive at a forecast. This forecast is converted into a visual representation in the form of a map.

External provider

DGMR

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