Urban greenspace and the indoor environment: Pathways to health via indoor particulate matter, noise, and road noise annoyance

William Mueller; Susanne Steinle; Juha Pärkkä; Eija Parmes; Hilkka Liedes; Eelco Kuijpers; Anjoeka Pronk; Denis Sarigiannis; Spyros Karakitsios; Dimitris Chapizanis; Thomas Maggos; Asimina Stamatelopoulou; Paul Wilkinson; James Milner; Sotiris Vardoulakis; Miranda Loh

doi:10.1016/j.envres.2019.108850

Urban greenspace and the indoor environment: Pathways to health via indoor particulate matter, noise, and road noise annoyance

Environ Res. 2020 Jan:180:108850. doi: 10.1016/j.envres.2019.108850. Epub 2019 Oct 22.

Authors

William Mueller¹, Susanne Steinle², Juha Pärkkä³, Eija Parmes³, Hilkka Liedes³, Eelco Kuijpers⁴, Anjoeka Pronk⁴, Denis Sarigiannis⁵, Spyros Karakitsios⁵, Dimitris Chapizanis⁵, Thomas Maggos⁶, Asimina Stamatelopoulou⁶, Paul Wilkinson⁷, James Milner⁷, Sotiris Vardoulakis², Miranda Loh²

Affiliations

¹ Institute of Occupational Medicine, Edinburgh, UK; London School of Hygiene & Tropical Medicine, UK. Electronic address: will.mueller@iom-world.org.
² Institute of Occupational Medicine, Edinburgh, UK.
³ VTT Technical Research Centre of Finland, Finland.
⁴ TNO, Netherlands.
⁵ Aristotle University of Thessaloniki, Greece.
⁶ National Centre for Scientific Research 'Demokritos', Athens, Greece.
⁷ London School of Hygiene & Tropical Medicine, UK.

PMID: 31670081
DOI: 10.1016/j.envres.2019.108850

Abstract

Background/aim: The exposome includes urban greenspace, which may affect health via a complex set of pathways, including reducing exposure to particulate matter (PM) and noise. We assessed these pathways using indoor exposure monitoring data from the HEALS study in four European urban areas (Edinburgh, UK; Utrecht, Netherlands; Athens and Thessaloniki, Greece).

Methods: We quantified three metrics of residential greenspace at 50 m and 100 m buffers: Normalised Difference Vegetation Index (NDVI), annual tree cover density, and surrounding green land use. NDVI values were generated for both summer and the season during which the monitoring took place. Indoor PM_2.5 and noise levels were measured by Dylos and Netatmo sensors, respectively, and subjective noise annoyance was collected by questionnaire on an 11-point scale. We used random-effects generalised least squares regression models to assess associations between greenspace and indoor PM_2.5 and noise, and an ordinal logistic regression to model the relationship between greenspace and road noise annoyance.

Results: We identified a significant inverse relationship between summer NDVI and indoor PM_2.5 (-1.27 μg/m³ per 0.1 unit increase [95% CI -2.38 to -0.15]) using a 100 m residential buffer. Reduced (i.e., <1.0) odds ratios (OR) of road noise annoyance were associated with increasing summer (OR = 0.55 [0.31 to 0.98]) and season-specific (OR = 0.55 [0.32 to 0.94]) NDVI levels, and tree cover density (OR = 0.54 [0.31 to 0.93] per 10 percentage point increase), also at a 100 m buffer. In contrast to these findings, we did not identify any significant associations between greenspace and indoor noise in fully adjusted models.

Conclusions: We identified reduced indoor levels of PM_2.5 and noise annoyance, but not overall noise, with increasing outdoor levels of certain greenspace indicators. To corroborate our findings, future research should examine the effect of enhanced temporal resolution of greenspace metrics during different seasons, characterise the configuration and composition of green areas, and explore mechanisms through mediation modelling.

Keywords: Air pollution; Exposome; Greenspace; Noise annoyance; Particulate matter.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Air Pollutants
Air Pollution, Indoor*
Environmental Exposure / statistics & numerical data*
Greece
Netherlands
Noise*
Odds Ratio
Particulate Matter*

Substances

Air Pollutants
Particulate Matter