Integrated Modelling for Health and Environmental Impact Assessment of Air Pollution and Climate Change

Modelling the impacts of air pollution and climate change on human health and ecosystems
in integrated assessment models (IAMs) has emerged as a key tool to inform policy
decision making, where simplistic solutions are unlikely to deliver efficient and sustainable
pathways for future development.
Model integration is facing a complex set of challenges in different dimensions, as
integrated models have to be:
Spatially explicit and of sufficiently high spatial resolution for their respective domain,
with nesting approaches providing the integration across different spatial scales.
Temporally dynamic to model system responses and recovery e.g. pollutant
accumulation, time-lag (e.g. of measure implementation) and time-bomb effects. Due
to different temporal horizons for different processes (e.g. days-years for air pollution,
decades-centuries for climate change, centuries-millennia for accumulation of heavy
metals/POPs in soils), integrated models also need to nest models with different
temporal resolution.
Sectorally detailed to model trade-offs and synergies and to allow for the
representation of paradigm-shifts (e.g. in energy systems) and behavioural changes
(e.g. non-technical measures).
Accessible, providing clear illustrations of inter-sectoral synergies and tradeoffs (e.g.
ammonia emission reduction vs. nitrate leaching in agriculture) using visualisations
and multi-media.
In addition to the aforementioned requirements, integrated models need to be flexible and
scalable to be able to provide answers to varying problems. This paper discusses current
challenges faced by IAMs and emerging developments based on a literature review.