Improving local air quality in cities: To tree or not to tree?

Abstract

Vegetation is often quoted as an effective measure to mitigate urban air quality problems. In this work we demonstrate by the use of computer models that the air quality effect of urban vegetation is more complex than implied by such general assumptions. By modelling a variety of real-life examples we show that roadside urban vegetation rather leads to increased pollutant concentrations than it improves the air quality, at least locally. This can be explained by the fact that trees and other types of vegetation reduce the ventilation that is responsible for diluting the traffic emitted pollutants. This aerodynamic effect is shown to be much stronger than the pollutant removal capacity of vegetation. Although the modelling results may be subject to a certain level of uncertainty, our results strongly indicate that the use of urban vegetation for alleviating a local air pollution hotspot is not expected to be a viable solution.

Introduction

Because of its adverse effect on human health, air pollution is an environmental problem of major concern. Due to the high traffic density, cities often face increased concentrations of air pollutants in comparison with its surroundings. In order to mitigate these air pollutant problems, the use of urban vegetation is often promoted as an effective measure to reduce concentrations. This measure is based on the underlying argument that trees (and vegetation in general) have the capability of cleaning the air by filtering out the pollutants. Vegetation leaves absorb gaseous pollutants through their stomata, while particles are removed from the air by deposition onto the leaves and the branches. Different studies (Beckett et al., 2000; Freer-Smith et al., 2005; Lovett, 1994) have experimentally assessed the deposition rate at which pollutants are taken up by the urban vegetation. However, Litschke and Kuttler (2008) pointed out that the uncertainty associated to the published values is still large.

Nowak and Crane (2000) have developed a deposition model that is able to estimate the pollutant removal capacity of a so called ‘urban forest’. Many studies using this model have reported impressive mass removal estimates for different cities (McPherson et al., 1994; Nowak et al., 2002; Tallis et al., 2011) in order to demonstrate the beneficial effect of urban green on the air quality. However, the resulting decrease in ambient concentrations is much less reported and if so, the effect of the urban forest on the city averaged air quality appears to be rather limited, often not exceeding an improvement of 1–2% (Tallis et al., 2011). In addition, Pataki et al. (2011) recently argued that there is lack of empirical evidence that support the findings of these deposition model simulations thereby concluding that the air quality benefit of urban green may be overestimated.

Although subject to a certain level of uncertainty, this city scale mitigating capacity of urban trees is merely one part of the story. Despite the fact that they effectively remove pollutants from the air, urban trees may under certain circumstances induce a local increase of concentrations. It has been shown (Gromke, 2011; Gromke and Ruck, 2007, Gromke and Ruck, 2009, Gromke and Ruck, 2012; Wania et al., 2011) that trees in urban street canyons obstruct the wind flow thereby reducing the ventilation leading to higher pollutant concentrations. This potentially negative effect of vegetation on the local air quality is much less known amongst policy makers and the broad public. Based upon the general idea that trees clean the air, there still is the misconception that trees are good for air quality in all cases and under all circumstances. Therefore policy makers and urban planners when faced with a local air pollution hotspot, often intuitively reach for trees to alleviate the problem, thereby potentially aggravating the situation.

The study presented in the current paper may be viewed in light of this. The initial goal was to investigate how urban vegetation can be used to improve the local air quality on inner city roads with busy traffic. The study consisted of two parts. In the first part, we conducted a sensitivity analysis where we analysed how different parameters (building geometry, pollutant type, wind conditions and vegetation type, size, position, porosity, filtering capacity) influence the impact of roadside vegetation on the local air quality. In the second part, we assessed the effectiveness of 19 different green street designs, designed by urban planners for actual implementation in various cities within Belgium and the Netherlands in order to improve the air quality. Throughout this paper, we will refer to the first part as the sensitivity analysis and to the second part as the case studies. The entire study was based on computer modelling using the micro-scale model ENVI-met (Bruse and Fleer, 1998).

Although similar studies (Gromke et al., 2008; Buccolieri et al., 2011; Wania et al., 2011) have been published before, from a scientific point of view the current study differs in the following sense:

• Focus on multiple and traffic related pollutants. Previous studies are often limited to a single and non-traffic specific pollutant such as PM₁₀.

• Different types of vegetation. We do not only consider trees but also study hedges and green barriers.

• Beyond idealised street canyon geometries. We also focus on an idealised non-street canyon case (detached building geometry) and study various real life geometries.

The paper is structured as follows: Section 2 describes the general modelling methodology. The sensitivity analysis and the case studies are presented respectively in Section 3 and Section 4. In Section 5 we discuss the results and draw the conclusions.