NEW DELHI: Every commuter knows the frustration of waiting at a red light. Engines hum, fuel burns, and nothing moves. What is less visible—but far more damaging—is the pollution released during those idle minutes. A new study by researchers at the CSIR–Central Road Research Institute (CRRI) shows that traffic intersections in Delhi are not just congestion points; they are air pollution hotspots that quietly waste fuel and expose thousands of people to harmful emissions every day.
Vehicle idling occurs when an engine is running but the vehicle is stationary—typically at traffic signals. Though each stop may last only seconds or minutes, the cumulative impact is enormous in a city like Delhi, where traffic volumes are high and signal delays are frequent.
The CRRI study estimates emissions and fuel losses at three busy signalised intersections—CRRI Gate on NH-2, Lodhi Road, and ITO—using real traffic data collected over 48 hours in both summer and winter. The results showed that weekday traffic is consistently higher than weekend traffic, leading to significantly greater fuel consumption and emissions on working days.
Carbon dioxide (CO₂) made up nearly 98% of total emissions, followed by carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons, and particulate matter (PM2.5). These pollutants are closely linked to respiratory diseases, heart conditions, and premature death—risks faced not only by drivers but also by pedestrians, traffic police, street vendors, and nearby residents, said the study published in reputed journal Current Science.
Urban roads have two main components: mid-block stretches and intersections. While vehicles move relatively freely on mid-blocks, intersections force vehicles to stop, queue, and idle, making them disproportionately polluting.
The problem is compounded in Indian cities by heterogeneous traffic—a mix of cars, two-wheelers, three-wheelers, buses, and trucks sharing the same road space without strict lane discipline. This space-sharing behaviour makes pollution prediction far more complex than in developed countries, where traffic is largely lane-based.
Internationally used air pollution models often struggle to capture this complexity. To address this, the CRRI team tested and calibrated CAL3QHC, a Gaussian dispersion model approved by the US Environmental Protection Agency (EPA), using Delhi-specific traffic and meteorological data.
Delhi is not unique in facing pollution linked to traffic intersections. Cities across the world have examined this issue and adopted different strategies to address it, with varying success, noted the authors—Niraj Sharma, Mukti Advani and Rajni Dhyani from the Transportation Planning and Environment Division, CSIR–Central Road Research Institute, Delhi.
United States (Brooklyin & Cincinnati)
In United States in cities like Brooklyn and Cincinnati, CAL3QHC and similar models have been used to predict carbon monoxide levels at intersections. Studies showed that pollution peaks during peak traffic hours and that surrounding buildings—known as “street canyon effects”—can trap pollutants. In response, several US cities have promoted anti-idling laws, with fines for vehicles that idle beyond a set time.
China’s Shanghai
Research at signalised intersections in Shanghai found that traditional models under-predicted pollution because they failed to account for mixed traffic and high-rise buildings. The city responded by investing heavily in signal coordination, electric public transport, and traffic demand management, helping to reduce both congestion and emissions.
Brazil (Belo Horizonte and Maringá):
Studies using CAL3QHC showed mixed results, with model accuracy strongly dependent on emission factors. This led to improved local emission inventories and greater use of roundabouts, which reduce stopping time and fuel consumption.
Hong Kong:
At busy intersections in Mong Kok, researchers used box models incorporating speed-dependent emission factors. The city’s dense urban form led planners to prioritise pedestrianisation, public transport, and strict vehicle controls, significantly cutting roadside pollution exposure.
Europe:
Cities such as Paris, London, and Stockholm have gone a step further by combining congestion pricing, low-emission zones, and intelligent traffic systems (ITS). These measures reduce traffic volume itself, lowering the need for vehicles to idle at signals.
What the Delhi study found
Using detailed traffic counts, fuel surveys, and air quality data from CPCB monitoring stations, the CRRI study estimated both idling emissions (during red signals) and free-flow emissions (once vehicles start moving).
Key findings include:
- Weekday emissions were substantially higher than weekend emissions at all three intersections.
- Pollution levels varied by season, with winter often showing higher concentrations due to poorer dispersion conditions.
- The “zone of influence” of an intersection—where pollution levels remain elevated—extended up to 300 metres in some locations.
- The CAL3QHC model performed satisfactorily overall, particularly for carbon monoxide, though it tended to under-predict pollution levels, especially PM2.5.
One major limitation identified was the lack of India-specific idling emission factors, forcing researchers to rely on international guidelines such as those from the Intergovernmental Panel on Climate Change (IPCC).
Why modelling matters for policy
Air quality models are not academic exercises—they inform real-world decisions. In many countries, model outputs guide:
- Traffic signal design
- Placement of schools and hospitals
- Exposure limits for roadside workers
- Urban planning and road redesign
For Delhi, the study shows that managing intersections more efficiently could deliver immediate air quality benefits—often at lower cost than large infrastructure projects.
What can be done: lessons from global best practices
The study points to several practical solutions, many of which have already proven effective internationally:
- Traffic signal synchronisation
Coordinating green lights across corridors reduces stop-and-go traffic. Cities like Singapore and London have cut delays and emissions significantly using adaptive signal control. - Roundabouts instead of signals
Where feasible, replacing traffic lights with roundabouts improves flow and cuts idling. Countries such as France and the Netherlands have long favoured this approach. - Anti-idling awareness and enforcement
In Canada and parts of the US, drivers are encouraged—or legally required—to switch off engines during long red lights. - Intelligent Transport Systems (ITS)
Real-time traffic management using sensors and AI can adjust signals dynamically based on congestion levels. - Cleaner vehicles and fuels
Expanding electric buses, CNG fleets, and last-mile public transport reduces emissions even when vehicles are forced to stop. - Stronger public transport
Cities that shift commuters from private vehicles to buses, metros, and trams see long-term reductions in congestion and intersection pollution.
The larger message
The Delhi study reinforces a simple but powerful idea: air pollution is not only a tailpipe problem—it is a traffic management problem. Intersections, where vehicles idle and people congregate, deserve far greater attention in urban air quality planning.
By adapting international models to Indian conditions and learning from global experiences, cities like Delhi can design smarter, cleaner, and healthier streets. Reducing idling at traffic signals may not sound dramatic—but in a megacity, it could make a measurable difference to both air quality and public health.
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