The potential to capture additional air pollutants by introducing more vegetation or changing existing short vegetation to woodland on first sight provides an attractive route for lowering urban pollution. Here, an atmospheric chemistry and transport model was run with a range of landcover scenarios to quantify pollutant removal by the existing total UK vegetation as well as the UK urban vegetation and to quantify the effect of large-scale urban tree planting on urban air pollution. UK vegetation as a whole reduces area (population)-weighted concentrations significantly, by 10% (9%) for PM2.5, 30% (22%) for SO2, 24% (19%) for NH3 and 15% (13%) for O3, compared with a desert scenario. By contrast, urban vegetation reduces average urban PM2.5 by only approximately 1%. Even large-scale conversion of half of existing open urban greenspace to forest would lower urban PM2.5 by only another 1%, suggesting that the effect on air quality needs to be considered in the context of the wider benefits of urban tree planting, e.g. on physical and mental health. The net benefits of UK vegetation for NO2 are small, and urban tree planting is even forecast to increase urban NO2 and NOx concentrations, due to the chemical interaction with changes in BVOC emissions and O3, but the details depend on tree species selection. By extrapolation, green infrastructure projects focusing on non-greenspace (roadside trees, green walls, roof-top gardens) would have to be implemented at very large scales to match this effect. Downscaling of the results to micro-interventions solely aimed at pollutant removal suggests that their impact is too limited for their cost–benefit analysis to compare favourably with emission abatement measures. Urban vegetation planting is less effective for lowering pollution than measures to reduce emissions at source. The results highlight interactions that cannot be captured if benefits are quantified via deposition models using prescribed concentrations, and emission damage costs. This article is part of a discussion meeting issue ‘Air quality, past present and future’.

中文翻译：

---

植被缓解空气污染的潜力和局限性以及基于沉积的评估的不确定性

通过引入更多植被或将现有的矮植被改变为林地来捕获额外空气污染物的潜力为降低城市污染提供了一条有吸引力的途径。在这里，大气化学和运输模型与一系列土地覆盖场景一起运行，以量化英国现有总植被和英国城市植被对污染物的去除，并量化大规模城市植树对城市空气污染的影响。英国植被作为一个整体显着降低了面积（人口）加权浓度，PM2.5 降低了 10% (9%)，SO2 降低了 30% (22%)，NH3 降低了 24% (19%) 和 15% (13%) ) 对于 O3，与沙漠场景相比。相比之下，城市植被仅将城市 PM2.5 的平均水平降低了约 1%。即使将现有开放城市绿地的一半大规模改建为森林，也只能将城市 PM2.5 再降低 1%，这表明需要在城市植树的更广泛效益的背景下考虑对空气质量的影响，例如关于身心健康。英国植被对 NO2 的净收益很小，甚至预测城市植树会增加城市 NO2 和 NOx 浓度，这是由于与 BVOC 排放和 O3 变化的化学相互作用，但细节取决于树种选择。通过外推，以非绿色空间（路边树木、绿化墙、屋顶花园）为重点的绿色基础设施项目必须以非常大的规模实施才能达到这种效果。将结果缩小到仅针对污染物去除的微干预表明，它们的影响太有限，无法进行成本效益分析，无法与减排措施相提并论。与从源头减少排放的措施相比，城市植被种植在降低污染方面的效果较差。如果使用规定的浓度和排放损害成本通过沉积模型量化收益，则结果突出了无法捕获的相互作用。本文是讨论会问题“空气质量，过去现在和未来”的一部分。如果使用规定的浓度和排放损害成本通过沉积模型量化收益，则结果突出了无法捕获的相互作用。本文是讨论会问题“空气质量，过去现在和未来”的一部分。如果使用规定的浓度和排放损害成本通过沉积模型量化收益，则结果突出了无法捕获的相互作用。本文是讨论会问题“空气质量，过去现在和未来”的一部分。