First Ever System of Air Quality Forecasting and Research- A Success

By - Kalpana Palkhiwala, Deputy Director(M & C), Press Information Bureau, New Delhi

System of Air Quality Forecasting and Research (SAFAR) is an operational air pollution forecasting service for the citizens of Delhi. Several interesting results have emerged from this system which was dedicated prior to the Commonwealth Games in September 2010 to the city.

SAFAR provided information to the public services and local people about the current level and forecasted (24 hours in advance) the level of air quality at various key locations of Common Wealth Games (CWG) through wireless LCD and LED display panels installed at 20 different locations in Delhi. This initiative has increased the awareness among general public regarding the air quality and allowed them to take appropriate preventative measures due to its forecasting ability. Continuous monitoring and forecasting is done for the major gaseous pollutants namely ozone (O3), oxides of Nitrogen (NOx), Carbon monoxide (CO), Benzene and other hydrocarbons as well as the Particulate Matters(PM) of 2 different sizes represented as PM10, PM2.5, and Black carbon. Out of the above, the forecast for the 5 pollutants namely O3, NO2, CO, PM10 & PM2.5 is displayed in terms of “Air Quality Index (AQI)” at a scale of 0-500. The AQI is based on the health effects of each of the pollutant which was based on the extension of the work related to national ambient air quality standards released by Ministry of Environment and Forest (MoEF) in November 2009. Using these MoEF standards and by fixing the break points and applying the mathematical formulations, scientists have defined the concept of AQI forIndia which facilitated its easy communication with the common man. The AQI calculation is country specific and exists in almost all those countries where such a prediction system exists. The air quality is defined in 4 broad ranges starting from Good (AQI: 0-100), Moderate (100-200), Poor (200-300) and Very Poor (above 300).

Overall Assessment of Air Quality

The Air quality was found to be of the mixed nature in the above AQI scale but not as bad as speculated by some quarters prior to the games period. Preliminary scientific evaluation of the data was generated from air chemistry transport forecasting model as well as from the dense network of monitoring stations in Delhi for various games venues. The data was classified in 3 time frames namely (i) before (2-3 weeks), (ii) during (3-14 Oct) and (iii) after (2 weeks) of the Common Wealth Games-2010.

The Air Quality in Delhi from September 2010 until now has hardly touched the "Very Poor" category. The overall assessment of air quality during September-October 2010 revealed that majority of gaseous pollutants were in good range, sometimes crossing moderate ranges in some venues during peak traffic hours. The air quality related to Particulate Matters (PM-2.5 and PM-10) was in good to moderate range before the games until the downpour but as the sun started shining it drifted to moderate. During the Games, most of the time the Air Quality Index for PM-2.5 was in moderate to poor range whereas PM-10 was mostly in poor category at alll the monitoring sites except at few venues and during some part of the night time. Benzene was found mainly well within the permissible limit. After the Games, the overall Air Quality slightly deteriorated, especially for Particulate Matters (in particular PM-10) which remained in the poor category, as was expected after the removal of traffic restrictions, the wind blown dust from paved and unpaved roads and increase in fossil fuel combustion. The wind blown dust mainly affects coarser particles and hence PM-10 is more affected.

Science Based Assessment of Air Quality in Delhi

Before Games: The relatively low level of PM-2.5 and PM-10 before games could be attributed to prevailing meteorological condition (heavy rains and cloudy conditions) which minimized the windblown dust emissions and also caused washout of PM-10 and PM-2.5. The dust originating from the construction activities could have deteriorated the PM-10 level but excess rain has helped it to settle down quickly. The photochemical formation of ozone was also reduced because of overcast sky conditions in spite of moderately high NO2 level, keeping ozone level in good range. This was quite satisfactory as surface ozone is one of the most toxic gase which is responsible for majority of the respiratory system related diseases like asthma, chest congestion, etc., a well established fact in Delhi as reported by epidemiologist due to the rush in hospital admissions and OPD visits increase when high ozone emission are noticed.

During Games: The AQI was found to be mostly in poor range for Particulate Matters and in moderate range for ozone. The increase in the level of Particulate Matters, especially PM10 during the games period as well as ozone was due to the clear sky and stagnant wind conditions, which lead to accumulation of Particular Matter in the boundary layer and more photochemical ozone formation. Moreover, due to the dry soil with sunny days, the emission of coarser particles, specially PM-10 has increased significantly through windblown dust from paved and unpaved roads supported by fast moving traffic but contribution of fossil emissions was in check (up to certain extent) due to traffic restrictions as a result PM-2.5 level were found relatively better. Air quality scenario showed relatively poorer air quality at Major Dhyanchand National Stadium, Talkatora Garden and Commonwealth Games village as compared to some areas like Pusa and NCMRWF (Noida) where long range transport from neighbouring states normally plays a vital role but due to calm winds this effect was minimized.

It was interesting to note that PM-10 and PM-2.5 suddenly became very high in the night time (between 12 midnight to 3AM) at several venue sites which initially could not be forecasted by the model because it was suspected to be due to the artificial fogging (for insects and mosquitoes) of the area surrounding the stadiums, a purely localized effect which disappeared after the games. The regular fogging during the games at night showed unusual impact on the air quality at night.

After Games: The level of particulate matters mainly PM-10 further increased and is more or less in the upper limit of poor range during day time probably due to traffic rush hours. Traffic did increase the fossil fuel combustion but it appears that it has more severely affected the windblown dust emissions from paved and unpaved road because the magnitude of PM-10 level increased significantly than that of PM-2.5.

Test of Forecasting Ability of Safar

Most of the time the forecasting capabilities are restricted due to lack of high resolution emission inventories of the pollutants. Hence for the air quality forecasting during CWG-2010, for the first time, a high resolution gridded emission inventory for 2009-2010 was developed and released just before the games. The accuracy and reliability of these inventories were validated using air quality forecasting model and its validation through monitoring network. The model validation provided a reasonably satisfying result well within the acceptable error for gaseous pollutants baring a few unexpected localized exceptions like the fuming impact in stadium during nights.

In case of Particulate Matters, when the emission inventory was used without accounting for windblown dust from paved and unpaved road and construction activities, the forecasting model greatly underestimated the observations mainly the PM-10 level. It was not used initially because it involves high amount of uncertainty and is hardly considered as significant source earlier by any modeler. However, scientists prepared it by collecting the relevant activity data but released separately as supplement to the original report because of its highly uncertain nature where the magnitude of its emissions was calculated to be very close to the sum of all other sector including transport, industry, bio-fuel, etc. However, when forecasting model accounted for this sector, the results of Particulate Matter were found to reproduce the observed data reasonably well. The air quality forecast from SAFAR system is found to be within 10% to 20% confidence limit of observations. Forecast model is also able to resolve the diurnal pattern quite satisfactorily.

Through this sensitivity test, it was seen that unnoticed sectors of windblown dust from paved and unpaved roads and construction activities is one of the major contributors in PM and some time even stronger than fossil fuel combustion from transport sector and hence need attention. The calm winds, temperature inversion and formation of relatively stable and persistent boundary layer during and after the CWG games played a vital role in distributing the level of air pollution and kept the dominance of localized effect and minimized the effect of transport from neighbouring states.

In addition to emissions, the air quality forecasting is highly influenced by meteorology and hence the SAFAR system first validated weather parameters obtained from the model with that of Automatic Weather Stations (AWS) monitoring network of India Meteorology Department and Indian Institute of Tropical Meteorology, Pune prior to air quality forecast. Hence, the air pollution problem and its forecasting services would be best served by simultaneously dealing with meteorological parameters and its forecast rather than dealing in isolation for planning of scientifically tenable mitigation strategies. (PIB Features)

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