Variation of Site Specific Pollutants with Vehicular Traffic in New Delhi: A Case Study

Monday, 15 December 2014
Srijan Aggarwal, University of Alaska Fairbanks, Fairbanks, AK, United States and Anuradha Shukla, Central Road Research Institute, New Delhi, India
Delhi, capital of India, is one of the most important polluted urban areas in the world. With a population of about 16 million, and an annual average growth rate of 3.85%, a rapidly increasing number of vehicles (more than 7.4 million, with an annual average growth rate of 7.27%, as reported by the Economic Survey of Delhi, 2012–2013), Delhi is facing an aggressive rise in vehicular pollution. Ground-level traffic vehicles in Delhi are typically natural gas fueled, gasoline fueled or diesel-fueled. The traffic-related air pollutants [particulate matter (PM), ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), lead (Pb), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs)] have huge impact on the health of the population given high exposure risk for daily commuters.

We conducted on-roadway ambient monitoring on National Highway-2 (NH-2; Delhi–Mathura Road), on the southeast outer zone of Delhi represented by heterogeneous traffic during heavy traffic hours in the morning and early evening, with varying vehicle speeds ranging 35-60 km/h. Ambient levels of PM2.5, PM10, O3, NOx, CO, CO2, black carbon (BC), and certain VOCs (benzene, xylene, ethylbenze) were recorded. In addition, traffic volume count surveys were carried out to record the number of vehicles in different hours of the day, moving across the count point during a given time. Specific traffic volume counts were also conducted at the location to understand the flow of traffic. Vehicle counts classified the vechicles into separate categories: buses (9.1%), trucks (9.2%), cars (41.6%), two-wheelers (30.3%), auto-rickshaws (6%) and other non-motorized traffic (3.9%). Statistical models have been developed to predict on-roadway pollutant concentrations in terms of specific vehicle counts, and weather parameters (temperature, wind speed). Results suggest that two-wheelers and auto-rickshaws significantly impact PM concentrations. Concentrations of BC are a strong function of heavy duty traffic (buses and trucks), two-wheelers and cars. Ozone and CO2 have a strong temperature dependence while NO2 concentrations are a function of both temperature and wind parameters. Wind speed was identified as a key parameter in majority of the prediction models that were developed.