Mapping mental wellbeing and air pollution: a geospatial data approach

Ecclestone, M and Johnson, T ORCID: https://orcid.org/0000-0002-1702-0943, 2026. Mapping mental wellbeing and air pollution: a geospatial data approach. ISPRS International Journal of Geo-Information, 15 (4): 142. ISSN 2220-9964

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Abstract

Urban air pollution is increasingly recognised as a determinant of mental wellbeing, yet most existing studies rely on static exposure estimates and lack spatial granularity. This limits understanding of how pollutant-specific patterns influence psychological states in real-world settings. To address this gap, we integrate real-time environmental and physiological data from 40 participants using the DigitalExposome dataset, applying multivariate and spatial analysis techniques. Our findings confirm that Particulate Matter (PM2.5) exerts the strongest negative association with mental wellbeing while extending prior work by establishing a preliminary ranking of other pollutants Particulate Matter (PM10), Particulate Matter (PM1), Carbon Monoxide (CO), Nitrogen Dioxide (NO2), Ammonia (NH3). We applied statistical and spatial analysis methods, including heatmaps and Voronoi diagrams, to explore links between pollutants and wellbeing and compare the relative influence of air pollution and noise. This enabled identification of pollutant-specific hotspots and multi-level wellbeing patterns across individual, accumulated, and collective scales. These results demonstrate the value of spatial analysis for environmental health research and support targeted urban interventions, such as green space placement and traffic re-routing, to mitigate mental wellbeing risks.

Item Type:	Journal article
Publication Title:	ISPRS International Journal of Geo-Information
Creators:	Ecclestone, M. and Johnson, T.
Publisher:	MDPI
Date:	April 2026
Volume:	15
Number:	4
ISSN:	2220-9964
Identifiers:	Number Type 10.3390/ijgi15040142 DOI 2598137 Other
Rights:	© 2026 by the authors. Published by MDPI on behalf of the International Society for Photogrammetry and Remote Sensing. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Borcherds
Date Added:	27 Mar 2026 11:31
Last Modified:	27 Mar 2026 11:31
URI:	https://irep.ntu.ac.uk/id/eprint/55480

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