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Juggling with air pollutant data

Chance of meeting the new air pollutant emission targets have tremendously improved by considerable progress on how emissions from different sources are measured and estimated

Juggling with air pollutant data

This work makes a valuable contribution to the recent EU Air Policy review that aims to improve models integrating air quality and climate change data, to help develop more realistic information. Ultimately, these models will help reaching compliance with new emission targets.

Natural and man-made emissions affect air quality. Initiatives to reduce man-made emissions are continuously assessed. But, until now, it has been difficult to separate background emissions from other natural and biological sources. Thanks to results of the EU-funded NatAir project, “emissions estimates were considerably improved in many areas,” notes Rainer Friedrich , the project leader and a Professor at the Institute for Energy Economics and the Rational Use of Energy (IER) at Stuttgart University, Germany.

Friedrich adds: “Now our emissions results are being used by many atmospheric modellers.” For example, NatAir data was included in the CHIMERE chemistry-transport model, which produces daily forecasts of ozone, aerosols and other pollutants, and makes long-term simulations for emission control scenarios.

In assessing air quality and climate change Stefan Reis, Senior Scientist at the Centre for Ecology and Hydrology in Edinburgh, UK, says that “the quantification of natural and biogenic emissions is highly relevant, because anthropogenic emissions have been subject to more and more stringent controls.” It is therefore vital to understand such emissions in order to determine air quality. Reis explains: “with anthropogenic emissions being further reduced, natural/biogenic emissions may dominate the contribution to air pollution for some substances and regions.”

Air quality data alone, however, cannot be used directly to predict climate change, Alistair Lewis, Professor of Atmospheric Chemistry in the Department of Chemistry at York University, UK, explains. “Models of biogenic emissions are highly sensitive to climate variables, but in themselves they don’t provide a prediction of climate variability,” he remarked. Better modelling of biogenic emissions, and subsequently air quality, will not provide a ‘crystal ball’ for forecasting climate change. Instead, “Atmospheric models are often coupled dynamically to biogenic emission models so that the two can influence each other,” Lewis continues. He insists that as these relationships should be considered when developing policies, there is a need for accurate data.

The data requirement is key when imposing new emissions ceilings. For example, “the fact the biogenic emissions can influence levels of particulate matter - a regulated air pollutant - does mean that pragmatic lower limits for particulate matter should be set,” Lewis remarks. On the 7th May 2012, the EU set a new reduction target on particulate matter emissions of 20% compared to 2005 levels, and similar constraints on many other air pollutants including 40% for nitrogen oxides (NOx) and 30% for volatile organic compounds (VOCs).  The availability of new emission estimates can assist in better monitoring these and other targets for the future.

By Hywel Curtis


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This project has received funding from the European Union’s Horizon 2020 Programme for research, technological development and demonstration under grant agreement No 6419747th FWP