20 November 2013

Laurence Rouïl - policymakers now trust air quality models

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Air quality forecasts have become more accurate and will soon become as ubiquitous as weather reports

Air quality is a public health issue. As recently as last October, the World Health Organisation classified global outdoor air pollution as ‘carcinogenic to humans.’ This means that such pollution could cause cancer, alongside other proven effects such as an increase in mortality due to respiratory and cardiovascular pathologies during pollution peaks.

Now, an EU-funded research project, called MACC-II, has been developing air quality forecast models since 2011. Seven teams in Europe feed data to these models, capable of predicting air pollution concentration in the atmosphere. Laurence Rouïl, head of the environmental modelling and decision making department at INERIS, the French Institute for industrial environment and risk, talks to youris.com about the role of these models in influencing policy. As policymakers' confidence in air quality models increases, she explains, the fight against air pollution remains every citizen's business.

How do the air quality models work?
As an input, we use meteorological data, and estimated emissions from road traffic, central heating, agriculture, etc. All of this data is provided by each member state and reprocessed by the project’s emission experts. Our models simulate chemical reactions between pollutants, and the way these will be conveyed through the atmosphere. As an output, we forecast pollution concentrations. This is currently done up to three days ahead, and ultimately, the forecast will extend to up to four days in advance by 2014, when the model is fully operational. 

We cover Europe entirely, plus Turkey, with a spatial resolution of 25 by 25 kilometres. In 2014, this scale will improve up to 10 by 10 kilometres.

What use is currently made of air quality prevision?
In EU member States, regional agencies in charge of air quality management use the data to make their own forecast at the smaller scale of a city or a given area. It helps policymakers take measures such as encouraging drivers to reduce their speed in case of a possible pollution peak, for example.

Furthermore, the private sector can exploit the project data to develop specific services related to air quality, such as smartphone apps.

What is the true impact of air quality predictions on policymakers?
Let me be realistic. In this period of global economic crisis, political realities may override air quality policies, in particular when jobs are at stakes. But globally, there is a progress, thanks to more reliable monitoring and forecasting systems.

When they appeared, our models were first considered as hardly understandable ‘black boxes.’ Now, policymakers' confidence in these models is increasing. Their predictions are taken into account. As a result, the European regulations on air quality have become more stringent.

How has air quality evolved in Europe since these models were first implemented?
There has been a reduction of sulphur dioxide, an irritant gas causing acid rains, emitted by the industry. But globally, air quality in Europe has neither improved nor worsened during the last decade. Take ozone, for example, its peaks are a little less intense, but the average concentration has not decreased. [Ozone in excess in the lower atmosphere causes irritation of respiratory tract and eyes.]

It may be due to the fact that we have not taken into account all sources of pollution in management strategies. Or to incoming pollution from other parts of the world. Or, possibly, to global warming, which may hamper reduction efforts. For other pollutants, either the trend is the same, or we do not know it yet.

Can these models help solve the air pollution issue?
The fight against air pollution does not only depend on models and policymakers. We are all responsible for pollution when we overuse our cars or heat our homes with wood, which sounds green but emits soot particles in the atmosphere. Therefore, we all have to share the burden of reducing air pollution.

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