Finely honed Climate models are becoming increasingly useful in setting policy because they are being extended to take into account many more of the interactions that
matter. Shown here are the changes in annual average surface temperature, ranging from a cooling of 2°C (blue) to a warming of 2. 4°C (red), due to short-lived gases and
particles between 2000 and 2030 (left and centre columns) and due to long-lived gases between 2000 and 2050 (right column). Each row shows results for a different
model. Hatching indicates a statistical significance of 95% for the response. Source: Drew Shindell, NASA’s Goddard Institute for Space Studies
enough information for policymakers to properly
weigh up these different effects. Neither have we
clearly identified the key sectors around the world that
might provide win–win–win scenarios for people worried about climate, air quality and ecosystems.
However, scientific and computational advances in
climate modelling and validation over the last few
years now mean that we can do a much better job.
Models now include many more of the interactions
that matter: atmospheric chemistry that can predict
ozone concentrations as a function of the methane or
carbon-monoxide precursors; or aerosol physics for
multiple kinds of particles – those directly emitted, like
soot and mineral dust, and those created in the atmosphere from other emissions. More importantly, the
models now include myriad interactions: the chemistry
that takes place on the surface of dust aerosols that in
turn affects sulphates; the impact of increasing methane on atmospheric oxidation, which affects aerosol
concentrations; or the affects that aerosols have on
clouds or snow albedo.
We can therefore now start to directly answer the
questions that policymakers are raising – and some of
the results may be surprising.
In Europe, for instance, the use of coal for power
generation produces very little sulphate aerosol or
black carbon because of existing air-quality controls.
Thus, the only options for reducing the climate impact
of coal relate to specific reductions in coal burning or
investment in carbon capture and sequestration.
However, in India and China a lot of coal and biomass is burned in domestic settings where inefficient
low-temperature combustion and a lack of pollution
controls mean that the mix of emissions is much more
complicated – carbon dioxide, of course, but also large
amounts of carbon monoxide, black carbon and sulphates. Together, these emissions contribute strongly
to the “Atmospheric Brown Cloud” phenomenon and
to the appalling air quality in the region. This implies
that efforts to improve rural electrification for instance
– even if the power is generated in a modern coal power
plant – could still reduce net climate warming because
of the impacts on reducing ozone, methane and black
carbon. These kinds of strategies are already being
pushed by the Indian government because of the more
direct impact on indoor and regional air quality and to
reduce the deforestation associated with biomass collection, but a recognition of the net climate impact may
help bridge the current gaps in the international negotiations on a climate treaty.
Other surprises include the recognition that reducing methane emissions from whatever source has
important indirect impacts on a range of other drivers
and is a more effective strategy for short-term reductions in global warming than had been previously recognized. As we move forward, we should be able to
assess the net climate impact of any particular policy
given the changes in emissions that will result.
Like a full life-cycle analysis for judging the impact
on net emissions of a switch in energy-generation technologies, a full Earth-system analysis should become
the new standard in judging climate-policy proposals.
All climate models are wrong, but some of them are
useful, and by working more closely to answer the questions that are actually being posed by policymakers, we
can make them more useful still. ■
