A city of horns and highways: New model maps Delhi's noise

New Delhi: In Delhi, where a traffic signal can mean a chorus of horns, busy roads run alongside homes and hospitals, and elevated Metro tracks cut through densely built neighbourhoods, noise is an almost constant feature of urban life.

A new study conducted under the Council of Scientific and Industrial Research (CSIR) has now developed a model that combines geographical and real-time traffic data to map environmental noise across the city.

The study seeks to address the limitations of conventional noise-monitoring methods by integrating land-use and geographical factors with real-time traffic variables such as vehicle counts, speeds and honking. The approach could provide a more accurate and cost-effective way of predicting and mapping noise across a complex urban landscape such as Delhi.


Titled "Integrated land use regression (iLUR) model with road traffic characteristics for environmental noise prediction and mapping in urban regions with heterogeneous traffic conditions", the study uses Delhi as a case study to develop a framework that could help authorities understand the spatial and temporal distribution of noise and plan more targeted measures to control it.

The significance of the research lies in the nature of Delhi itself. Unlike cities where residential, commercial and industrial areas are more clearly separated, the capital has a highly mixed urban landscape.

As the study points out, residential colonies often sit alongside markets and commercial establishments, while schools and hospitals can be located close to busy roads. Different types of vehicles share the same roads, traffic conditions change through the day and honking is a prominent part of the city's traffic environment.

These characteristics make Delhi particularly difficult to study through conventional noise-monitoring methods.

To capture this complexity, researchers used noise observations from 201 locations across Delhi. The study also incorporated data on hourly traffic counts, vehicle speeds and honking events, along with information on roads, land use, population density, built-up areas, metro infrastructure, railway stations, bus stops and traffic crossings.

The monitoring exercise was carried out over nine months, from October 2023 to June 2024, allowing the researchers to account for seasonal variations in noise.

The study found that hourly traffic count was the most influential predictor of environmental noise across all four models developed. The number of honking events was also among the most influential predictors, particularly for daytime, 24-hour and day-night noise levels.

For a city such as Delhi, where road traffic is widespread and honking is frequently observed, the finding offers a more realistic picture of how noise is generated and distributed.

The models were developed to predict four different measures of noise : daytime noise, nighttime noise, 24-hour equivalent noise and day-night average noise.

The study then used these models to generate high-resolution noise maps for the New Delhi region. These maps provide a visual representation of how noise levels vary across the urban landscape rather than restricting assessment to individual monitoring stations.

The spatial variation was found to be strongly associated with residential and major roads. Commercial and residential land-use areas also contributed to the distribution of noise, while built-up areas affected the propagation of daytime and 24-hour noise.

At night, factors such as proximity to roads and railway stations became more important.

The findings also highlight why there cannot be a single solution to Delhi's noise problem.

A highway carrying large volumes of fast-moving traffic can have a different acoustic footprint from a residential road, while a busy crossing may generate noise through acceleration, deceleration and honking.

Elevated metro corridors can influence noise over larger distances, while commercial areas can become daytime hotspots because of the concentration of people and vehicles.

Even bus stops can have an indirect relationship with noise. The researchers found a negative association between the number of bus stops and noise levels. Roads with frequent bus stops can experience lower vehicle speeds, while high-speed traffic may shift to alternate routes with fewer stops.

This is where the study's Delhi-specific character becomes particularly important.

Rather than treating noise as a uniform phenomenon, the model attempts to capture the way the city's road network, traffic behaviour and land-use patterns interact.

The researchers say the resulting noise maps could be compared with Indian noise standards and international guidelines to identify areas where noise levels require greater attention.

"If traffic volume is the dominant factor in an area, traffic-management measures may be relevant. Where honking contributes significantly, enforcement and behavioural interventions could be considered. Where infrastructure such as highways or elevated metro corridors influences noise over larger areas, acoustic considerations could be incorporated into planning and design," said Saurabh Kumar, one of the researchers.

The model could also prove useful for assessing new urban infrastructure before it is built, particularly in a city that continues to expand its road and public transport networks.

That limitation points to another important finding from the exercise: better noise management in Delhi will depend not only on more sound-monitoring stations but also on better, continuously updated information about the city's traffic.

For a metropolis where traffic intensity, speed and honking can change sharply between peak and non-peak hours, a static assessment can provide only a limited picture.

"For Delhi, where air pollution is routinely measured and mapped, the study brings another form of pollution into sharper focus," Kumar said.

The study, he added, attempts to build a practical tool for understanding how a rapidly changing megacity sounds, and, eventually, how it can be made quieter.