Effective policies are based on a robust knowledge base and solid science

Article Published 15 Mar 2017 Last modified 11 May 2021
3 min read
At all governance levels, public policy making entails making decisions between different options and approaches. Some decisions, such as to invest in fossil fuels or renewables, might involve selecting one option over the other. Others might address the ‘how’ question – we will invest in renewables but which ones are the best for the society? Each policy decision results in outcomes, some of which might be unforeseen, unexpected or even detrimental to those whose lives it is supposed to improve. In the long term, the overall harm can be much larger than gains in the short term. To achieve the positive and lasting results on the ground, policy makers need to be able to make informed decisions, after assessing the benefits and costs of each available option.

An effective policy almost always relies on science. Similarly, measuring the effectiveness of a policy decision requires targets, which in turn entail a mechanism to monitor progress over time. Target setting and progress reporting also rely on scientific methods and evidence. These approaches are embedded throughout the European Union’s environment and climate policies. 

The EU’s air quality policies, for example, aim to reduce the harm caused by various air pollutants and pollution sources. Long-term exposure to even low doses of air pollution constitutes a health risk, affecting us all at varying degrees. Medical science has long confirmed the links between poor air quality and respiratory and cardiovascular diseases, impacting the young and the elderly in particular.

Science can identify causes and solutions

To monitor EU air pollution, Member States have set up more than 2 000 monitoring stations, regularly reporting the concentrations of various air pollutants in city centres, on roadsides or in rural areas. All this data is measured and processed in a way that is coherent across the EU and comparable over time. This reporting infrastructure allows policy makers to understand where and why there are pollution exceedances and helps inform what they can do to tackle it. Air quality modelling, informed by best science, is instrumental in identifying cause and effect relations, such as the number of diesel cars or coal-fired power plants and their impacts on urban air quality. This type of understanding is essential for designing appropriate policy responses and solutions.

At the local level, many cities have taken specific action to improve air quality. For example, the mayors of Paris, Madrid and Athens have proposed measures to ban diesel cars and vans from city centres by 2025 to improve air quality and reduce the associated damage to human health. Other cities struggling with repeated air pollution episodes are having to consider similar actions.

Trends can trigger action

In other cases, science-based evidence does not need to be time and location specific to provide reliable information, highly relevant to policy decisions. Informed policy decisions do not always need to be taken on the basis of complex spreadsheets listing hourly ozone readings at every monitoring station. Trend lines can equally strongly convey the message that action must be taken to reduce air pollution and its health impacts. Even with gaps in data, environmental and climate trends can send out a strong and convincing call for policy action. 

Although the scope of climate science, including the multiple impacts of climate change, is very broad and deals with a level of complexity, non-linear relations, tipping points and thus a number of uncertainties, its central findings are quite clear: our planet is warming and our dependence on fossil fuels contributes to this warming. We also know that certain regions, not only across the globe but also in Europe, will be more affected by the adverse impacts of climate change than others. These findings have triggered many ambitious policies both at EU and global levels, including the EU’s climate and energy targets for 2030 and the Paris Agreement under the United Nations umbrella.

In fact, uncertainty and data gaps do not undermine the validity of scientific conclusions. They are an integral part of science and are clearly acknowledged in assessments. By acknowledging potential weaknesses, scientific knowledge evolves continuously, improving its methods, models and analysis.

Improvements in scientific knowledge and progress reporting towards a policy target can lead to policy improvements, such as adjustments to testing methods of carbon dioxide emissions from cars and vans or setting more rigorous climate and energy targets for 2030.

Our core work at the European Environment Agency deals directly with conveying scientific knowledge to policy makers and the public. We are a knowledge institution at the centre of an extensive network (European Environment Information and Observation Network), bringing together experts from national institutions and other bodies across 39 European countries. The EEA provides independent and reliable information on a wide range of topics linked to Europe’s environment and climate. It helps compile data collected by its Member countries and ensures their quality. Based on this information, the EEA produces policy-relevant assessments to support policy making at European and national level with the aim to contribute to tangible improvements in citizens' lives.


Hans Bruyninckx

EEA Executive Director

The editorial published in the EEA Newsletter 01/2017, March 2017


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