CLIDEWO: Climate Change, Decent Work and Workers’ Health in Brazilian Agriculture
Climate change · Decent Work · Risk Assessment · Agriculture
Overview
Agricultural workers in Brazil face a compounding set of risks: climate change is intensifying heat, drought, and seasonal extremes across key farming regions at the same time as poor working conditions — including wage theft, bonded labour, and exposure to pesticides — leave workers without the protections or income buffers to adapt. CLIDEWO asks how these pressures interact: where are workers most exposed, which climate hazards most directly worsen labour conditions, and what do workers themselves identify as the most urgent risks?
The project conducts a worker-informed, data-driven climate risk and vulnerability assessment of agricultural workers in Brazil, combining quantitative climate and socio-economic modelling with systematic collection of worker voice data. Its aim is to support policy action on SDG 8 (decent work) in the context of accelerating climate change.
Methods
CLIDEWO uses a multi-layer risk assessment approach that integrates three types of evidence:
Climate models Downscaled climate projections for key agricultural regions of Brazil, identifying exposure to heat stress, drought, extreme rainfall, and other hazards relevant to outdoor agricultural labour.
Socio-economic data National labour market statistics, sectoral employment data, and existing administrative records on labour inspection outcomes, combined with geographic information on agricultural production systems.
Qualitative worker voice data Structured engagement with agricultural workers across partner regions, capturing worker perceptions of risk, adaptive capacity, and the specific ways in which climate and working conditions intersect in their daily experience.
These layers are integrated into a composite vulnerability assessment that identifies the populations and locations of greatest concern, and supports scenario analysis for policy recommendations.
Partners
Research institutions - Rights Lab, University of Nottingham - Universidade Federal Fluminense (UFF) - Universidade Federal de Mato Grosso (UFMT) - Universidade Federal do Maranhão (UFMA) - GPMAT
Funder British Academy — ODA Challenge-Oriented Research Grants 2024 Programme (IOCRG100945), via the UK Government’s International Science Partnerships Fund
Outputs
The project is producing openly available datasets, interactive data visualisations, and data science tools through the project website. Peer-reviewed outputs are in preparation.