Air-Health Team

Fire, Atmosphere, Air Quality, & Health

Wildfire smoke presents a significant and multifaceted public health challenge, demanding a comprehensive approach that encompasses increased knowledge, improved fire management, accurate air quality information, enhanced education, and robust healthcare readiness.

This team aims to address these complexities by exploring the effects of fires on atmospheric composition, surface-level air quality, and population health. Our focus includes refining the quantification and characterisation of gaseous and particulate emissions in smoke, linking them to human exposure and long-term health impacts, such as carcinogenic elements. Additionally, we examine broader health aspects, including the mental health of those regularly exposed to excessive smoke and the specific risks faced by practitioners directly involved in landscape fire management.
Organised into three work packages, the team aims to: (1) enhance and exploit top-down (or ‘direct’) methods developed within the Centre to improve fire emissions estimates; (2) understand the constituents of landscape fire smoke, both gases and particulates, and their controls through investigations involving real-world fires and laboratory experiments; (3) explore the connections between fires and public health, regionally and globally, with a focus on populations residing or working in severely fire smoke-polluted air.
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Fire-Veg Team

Fire-Vegetation Interactions: incorporating a realistic treatment of fire-vegetation interactions in the next generation of fire and earth system models.

Current approaches to modelling fire do not take account of the fact that most vegetation types are fire-adapted, but this varies with the nature of the fire regime. Similarly, current models also do not take account the flammability of the vegetation, even though it can be important for the type of fire

The goal of this team is therefore to develop a better understanding of vegetation-fire interactions and the implications of these interactions for fire modelling at a global scale. We will use these insights to develop a new fire-enabled vegetation model, suitable for coupling in a land-surface modelling scheme. It will allow us to explore how changing climate will affect fire regimes, and how this in turn will affect vegetation properties, biodiversity, and ecosystem post-fire recovery. It will also provide a platform for investigating management strategies for mitigating the effects of future changes on fire regimes.

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WHIRR Team

Wildfire risk, insurance, regulation and recovery

Insurance is a mechanism not just for financing recovery from wildfires, but also for incentivising risk reduction. However, those insurance mechanisms of risk management are struggling to cope with wildfires, whose frequency and severity are increasing in ways that are poorly understood, not least because of their dependence on loosely coupled and endogenous feedbacks with insurance and property markets, public expectations and behaviour, and with the political and regulatory systems for governing land use, insurance provision, and disaster financing.

This team will therefore answer questions on the role of insurance markets and other mechanisms prevention, protection, and recovery and sustainability from wildfires. For example: what influence do insurance incentives and government regulations for ‘hardening’ buildings and ‘fire-proofing’ the immediate landscape around houses have on wildfire risk, public attitudes and behaviour, insurance availability and cost?; how are insurance markets, and other mechanisms for protecting against losses and financing recovery from wildfire, responding to the changing risk, and what are the implications of this?; and how well does insurance serve the aims of covering losses, financing recovery, and providing the loss protection essential for functioning property markets and community sustainability?
Answering those research questions will involve an interdisciplinary programme of research integrating engineering science and statistical modelling combined with qualitative and survey research with insurance market actors, regulators and publics to understand the dynamics of insurance and wildfire risk.
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Just Fire Team

Just Fire: identifying equitable fire governance, livelihoods and futures.

The aim of this team is to promote ecologically sound and socially just approaches to fire management and governance that combine scientific and traditional knowledge systems and support the livelihoods and rights of Indigenous and local communities. To date, we have collected information on different forms of fire use, both at the global and local scales, and analysed it to understand general patterns, including recent human fire use at the regional and global scales, and the changing interactions between fire and the livelihoods and rights of Indigenous and local communities.

This team will build on this work, focusing on three themes, each of which will benefit from deep-dive research in one or more case study area: (1) Fire governanceanalysing whether and how fire is represented in international agreements and national laws, and how these constrain and/or enable local level fire governance; (2) Fires, livelihoods and biodiversity -explores the role of fire in mediating the relationship between cultural diversity and biodiversity; and (3) Future fire – asking how fire use is likely to change into the future, taking into account both climatic changes and potential governance responses to those changes.

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Info-System Team

Fire information System: A multi-decadal & NRT (Near Real Time) Fire Information System supporting the study of fire regimes, drivers, model representation and model development evaluation.

Modern Earth Observation (EO) datasets now span over two decades, and in some cases almost four decades, providing particularly extensive information on burned areas and hotspots. However, there are many uncertainties. For example, our longest record from AVHRR Global Area Coverage (GAC) EO data reveals fire regimes behaving inconsistently with climate-driven indices of increasing landscape flammability. The intricate patterns emphasise the urgency of developing a detailed understanding of the multifaceted nature of fire, grounded in independent and well-understood datasets.

The primary focus of this team is therefore analysis of multivariate EO data to investigate local to global scale fire behaviour, trends and anomalies, and to provide data and approaches to support the enhancement, further development and testing of fire representation in models. We aim to provide a holistic understanding of the nature of fire activity on Earth and where and how this is changing, supporting examination of its impacts and feedbacks and its potential evolution into the future. The team will help us understand and document fire activity on Earth over past decades, examine current trends, and identify future anomalies. Ultimately, we aim to enhance fire modelling by (i) enabling the rigorous testing of models against this observational dataset, and (ii), help develop process scale models by learning from EO data, thereby helping to construct robust, data-aligned models.

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Climate Team

Fire, Atmosphere and Climate

Wildfires lead to enormous quantities of pollutants emitted into the atmosphere, and the influence of this on atmospheric composition has been sporadically investigated for a variety of regions, using different approaches. However, a) there remains large uncertainty in those effects, b) there have not been any systematic assessments of fire impacts on atmospheric composition in a holistic way, from a global perspective, going beyond the fragmented single-region, single-constituent, or single-dataset approaches that have been taken so far.

This team will therefore advance the current understanding of the role of fire in the Earth system via atmospheric composition changes by thoroughly investigating uncertain processes and impacts of fire for the first time, through a novel approach that involves the synergistic use of atmospheric composition modelling, global climate modelling, and a range of targeted observational datasets. The focus will be on important short-lived constituents such as aerosols (black carbon and organic carbon), tropospheric ozone (O3) and its precursors (NOx, CO, CH4, VOCs) whose levels and distributions are challenging to model, and exert inhomogeneous radiative forcing.

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