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

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

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Free article

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

William Mueller et al. Environ Res. 2020 Jan.
Free article

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 PM2.5 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 PM2.5 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 PM2.5 (-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 PM2.5 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.

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