Work

Assessing the impact of data fusion and data quality on spatiotemporal characteristics of exposure models and probability maps - a case study for hazardous mineral fibres

Year: 2026

Type: article

Abstract: Exposure modelling for lesser-studied hazardous mineral fibres is complicated because data is scarce and fundamental knowledge of their distribution, dispersion, and health effects is limited. Despite growing concern of the health impacts associated with inhaling airborne mineral fibres, there are no standardised approaches for selecting, integrating, and resolving the diverse environmental datasets needed to build reliable exposure models. To address this gap, we develop a GIS-based data fusion workflow that tests how data type, quality, and integration method influence the spatial and temporal accuracy of exposure models and the probability maps they generate. The workflow was applied to a case study in El Dorado Hills (USA), where exposure is linked to the disturbance of naturally occurring asbestos. Historical fibre counts were cleaned, georeferenced, and integrated with multiple environmental datasets of varying spatiotemporal resolution. Our analysis shows that both model performance and resulting probability maps are highly sensitive to data fusion choices. Model outputs improved when input layers were refined or supplemented, and different fusion methods led to substantial variation in predicted exposure hotspots, even when using the same underlying data. These results highlight the complex interplay between data quality and the spatial patterns of predicted exposure. They demonstrate the importance of data quality and choice of integration strategy in determining the efficacy of exposure modelling approaches. Our workflow offers a reproducible framework for improving spatiotemporal exposure mapping in other settings where exposure-related health hazards remain poorly understood.

Source: Journal of Hazardous Materials Advances

DOI: 10.1016/j.hazadv.2026.101065

Authors: Dacey Zelman-Fahm, Katarzyna Sila-Nowicka, Jennifer A. Salmond

Institution: University of Auckland

Language: English

Topic: Occupational and environmental lung diseases

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,400