“Unique solution of the SAFAR framework for air quality management”
The Ministry of Earth Sciences’ System of Air Quality and Weather Forecasting And Research (SAFAR) project received a global nod for the first official Indigenous Air Quality Forecasting Framework in Delhi, Mumbai, Pune and Ahmedabad.
What is the framework developed by SAFAR to forecast air quality in the four metropolises?
The framework was first developed and implemented for Delhi in 2010, used in Pune from 2013 and in 2015 it was extended to Mumbai and Ahmedabad (2017). SAFAR has chosen to demonstrate its forecasting model in four different and contrasting microclimates of Indian cities.
The framework includes six developed elements, including data from the network of air quality and weather monitoring stations, emission inventory to track sources of pollution, air quality index , among others.
The chaotic nature and complexity of air pollution itself makes forecasting a difficult task, especially in a city heavily influenced by meteorology due to its geographic location, which is considered in this work. We use 24-hour measurements of air quality and meteorological parameters, as well as scientific analysis to improve forecasting capabilities.
The SAFAR framework takes into account almost all levels of pollutants (PM10, 1, 2.5, CO, NOx, SO2, volatile organic compounds, etc.) via automatic analyzers. With this framework, India will no longer need to depend on any international air quality forecasting framework. This is developed according to the micro-climatic conditions of the country. SAFAR’s forecasting model is comparable to the United States Environmental Protection Agency (US-EPA) framework.
What is the scope of the air quality forecast?
We can provide air quality forecasts 24, 48 and 72 hours in advance. And for extreme pollution events like dust storms or stubble burning issues, we’ve also launched a long-range forecast that gives a forecast five days in advance. The air quality parameters are very dynamic, they have a very short lifespan. Scientifically, it is not viable to give an air quality forecast more than five days in advance. From 2017 new things were added to it and other aspects of indigenization and awareness were added to the model.
How will forecasting air quality help citizens?
Using this forecasting model, all urban local agencies can issue timely health advisories to alert citizens in advance of poor air quality days, which will help protect vulnerable groups. serious health effects of air pollution. This framework is a unique solution for air quality management leading to mitigation, and also helps formulate micro-specific air action plans based on sound science. This framework can be easily replicated in 132 cities across the country with a population of over 10 lakh.
How many air quality monitoring stations are needed in a city like Bombay to get an accurate forecast?
A lot of people say there should be 100 or 200 monitoring stations in a metropolitan city. But I do not agree. It is hardly possible. These instruments are expensive. Once the base station requirement is met, money can be invested in mitigation measures rather than installing new instruments.
On the other hand, having an insufficient number of stations would give us biased data and not really represent the city. According to research from the World Meteorological Organization, where I was a representative of India, in a city where the population is between 50 lakh and 1 crore, a minimum of 10 to 12 stations is a requirement. Next is the location of stations, which depends on geography, land cover and land use. There are six micro-environments that should be covered, namely intersections, residential, industrial, upwind and downwind locations, and in a coastal city like Mumbai one should be near the coast.
What is the emission inventory and its role in predicting air quality?
An emissions inventory is nothing more than an account of all the sources of pollutants in a particular area at a given time. It details the amount and types of air pollutants released to the air and provides information on the types of sources that emit the pollutants and their location. This is the most important entry into the air quality forecasting model. This data is also crucial for policy determination, mitigation planners and micro-level planning.
It is important to understand that emissions in an area are not directly proportional to the air pollution levels in that area.
For example, there is an emission source in an area (combustion of fossil fuels), and the wind direction is east. Then a place which is even 3 km from this emission source will be highly polluted, while an area which is 500 meters west of the source will not register a high level of pollutants. The forecasting framework includes all of these elements.