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Introduction

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Introduction

ECMWF is leading a new initiative to explore the development of a European system to monitor human activity related carbon dioxide (CO2) emissions across the world. Such capacity is vital to support Europe’s leading role in worldwide action to address climate change. The CO2 Human Emissions (CHE) project started on October 2017, bringing together a consortium of 22 European partners and lasting for over three years.

Earth

 

The initiative will act as a bridge between the European Commission and its CO2 Task Forces, space agencies and related industries, the CO2 science community, and the Copernicus Services. The project aims to bring together relevant expertise to develop the science and to scope out the necessary architecture for a European CO2 monitoring capacity.

Supporting climate change policy

There is now agreement that climate change represents a very serious threat. Worldwide commitment to tackle the issue culminated in the United Nations Paris Climate Agreement in December 2016, when 195 nations signed-up to limit their greenhouse gas emissions.

However, to enable well-informed decision making for greenhouse gas emission reductions, and to monitor policy effectiveness, a comprehensive global greenhouse gas observing system is required. Monitoring carbon dioxide (CO2) has drawn most attention, due to its dominant role in climate change and the strong human hand in its emissions.

The challenges of developing a CO2 emissions monitoring support capacity

In 2015, a European Commission report considered a European capacity for monitoring anthropogenic CO2 emissions and concluded that a comprehensive observing system should be based on a combination of space-borne observations and ground-based monitoring networks.

The observing system must allow us to separate the impact of anthropogenic emissions from the effect of the complex natural carbon cycle, both affect atmospheric CO2 concentrations.

Observations from satellites, ground-based observation networks and aircraft provide CO2 information at specific times and locations, but alone do not constitute a continental to global monitoring capacity across different time scales. Moreover, these observations mostly measure atmospheric CO2 concentrations, which is an indirect measure of the underlying carbon emissions or uptake. Therefore, the use of an Earth System modelling infrastructure is required to combine Earth observations (ground-based, aircraft and satellite) with detailed CO2 emissions inventory data.

This is a very ambitious target, which is challenged by current limitations in observation availability, as well as in models and model-data fusion techniques. However, those are precisely the key system components needed to enhance our capacity to extract the anthropogenic contribution to rising CO2 concentrations and to enable the impact and effectiveness of policy-driven changes to be monitored.

Combining top-down and bottom-up techniques to study the carbon cycle

Studies of the carbon cycle tend to fall into two categories: ‘top-down’ and ‘bottom-up’.

In ‘top-down’ or ‘inverse’ techniques, measurements of CO2 concentration in space and time are used to infer the large-scale uptake and release of CO2 at the surface. However, they have clear difficulties in disentangling sources and sinks at local scales, and even bigger challenges in separating fossil fuel and other human-induced emissions from natural fluxes.

On the other side, ‘bottom-up’ approaches using process models and inventories can provide spatially heterogeneous information based on our knowledge of emission sources and their evolution over time. They can also incorporate our knowledge of biological processes that drive the exchange of CO2 between the atmosphere and the land and ocean. However, these approaches still have significant errors and uncertainties especially when aggregated to the global scales.

A synergetic solution is therefore to be found through the combination of top-down and bottom-up approaches, by merging the available knowledge from emission inventories and process models with the increasing amount of observational data for the atmosphere and the Earth’s surface.