Opinion Why pollution control needs localised data, grounded in science

While anthropogenic pollution can be controlled, pollution from natural sources and processes that may vary in different climatic zones is almost inevitable. Air pollution mitigation actions could address climate change concerns and reduce health hazards. To effectively address air quality issues at the national level in an era of fragile climate, India needs to develop an indigenous, science-based, and credible air quality resource framework — an information mechanism to help decision-makers in government and the private sector. The office of the Principal Scientific Adviser to the Government of India is considering an ambitious initiative along this line. The framework should integrate information on sources of emissions with precise knowledge of air-sheds — an area where local topography and meteorology limit the dispersion of pollutants. Air quality forecasts should be combined with health advisories and mitigation strategies should be devised in short, medium, and long terms to help local, state, and national governments. In other words, a blend of science, policy and advocacy.

India has diverse micro-environments and climatic conditions vary according to regions. This means we need to understand a diversity of natural and scientific processes. Air quality management in India must be addressed at three levels — rural, urban, and industrial agglomeration. Currently, our efforts are largely confined to analysing observed air pollution data at the urban level. Then, there are policy implementation issues at the state and district levels.

The basic factors governing air quality in India are air-sheds, the baseline levels of pollutants in an area and dynamic factors — local weather and emissions. Two critical input parameters — an inventory of emissions and air-shed mapping — should be reinforced before embarking on the development of an air quality early warning framework. Indian cities are geographically diverse — they consist of different climatic zones with different air-sheds and dominant emission sources.

Therefore developing a pollution prediction system in India is more complex compared to the rest of the world. By baseline levels, we mean the ambient air pollution naturally present, without any anthropogenic sources of emission. It’s also a pollution level to which the local population is likely to adapt and develop immunity. NIAS researchers recently determined the first experimentally derived baseline levels of major air pollutants — PM10, PM2.5, NO2, ozone, CO, and SO2 — in cities in the different climatic zones of the country. The baseline level of PM2.5 vary from 20-40 µg/m3. They are much higher than the WHO guidelines numbers, suggesting that India should frame its standards based on its own findings.

Emission inventories are the basis for air pollution trends analysis, air quality modelling efforts, and regulatory assessments. An air quality forecasting system requires micro-planning and micro-environmental inputs. There is no systematic emissions inventory in India that can be periodically updated. This is one of the major shortcomings in India’s air quality management framework. This stems from a lack of accurate data and inadequate monitoring networks. Ground-based data in association with satellite-driven data and other new techniques should be used for forecasting. NIAS has recently used drone-based artificial intelligence to identify emission hot spots in Bengaluru — the first time this technology has been used for this purpose — and attempted to narrow down the uncertainty in emission estimates. Such experiments need to be extended to other cities. We need to explore the possibilities of “CubeSats” — a class of nano- and microsatellites. Local weather factors directly influence the dispersion, transformation, and accumulation of air pollutants shaping the quality of the air we breathe. Recognising and understanding this relationship is crucial for policymakers, urban planners, and environmental agencies.

We propose an indigenous science-based air quality resource framework. It should be stewarded by a consortium of domain experts, health scientists, policy specialists, communicators, and an outreach group to steer the air quality issues. This group should give recommendations to government bodies on all aspects of air quality science and management. In other words, we propose an integrated mechanism that translates data into information, frames communication strategies and health advisories, issues alerts and plans mitigation strategies. We also underline the need for a centralised emissions dataset as per international norms. There should be more robust application of data from Indian satellites to air quality science. Data collection methodology, reporting protocols and database for the emission inventory should be standardised. Emerging technologies like drone-based unmanned aerial vehicles and CubeSats should be deployed. The 15th Finance Commission provided enough funds to states for air quality management. State agencies need to work in tandem with academic and research establishments to develop forecasting systems and operationalise them. The proposed consortium should be especially relevant in providing scientific recommendations and area-specific recommendations at the state and district level.

Beig is a Chair Professor at NIAS and Founder Director, SAFAR@IITM (MoES). Nayak is Director NIAS and Former Secretary, Ministry of Earth Sciences. The article is based on a policy brief of NIAS by the authors on “Air quality forecasting and resource framework”