4.7 Article

Urban particulate pollution reduction by four species of green roof vegetation in a UK city

期刊

ATMOSPHERIC ENVIRONMENT
卷 61, 期 -, 页码 283-293

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.atmosenv.2012.07.043

关键词

PM10; Green roof; Sedum; Magnetic biomonitoring

资金

  1. NERC

向作者/读者索取更多资源

Urban particulate pollution in the UK remains at levels which have the potential to cause negative impacts on human health. There is a need, therefore, for mitigation strategies within cities, especially with regards to vehicular sources. The use of vegetation as a passive filter of urban air has been previously investigated, however green roof vegetation has not been specifically considered. The present study aims to quantify the effectiveness of four green roof species - creeping bentgrass (Agrostis stolonifera), red fescue (Festuca rubra), ribwort plantain (Plantago lanceolata) and sedum (Sedum album) - at capturing particulate matter smaller than 10 mu m (PM10). Plants were grown in a location away from major road sources of PM10 and transplanted onto two roofs in Manchester city centre. One roof is adjacent to a major traffic source and one roof is characterised more by urban background inputs. Significant differences in metal containing PM10 capture were found between sites and between species. Site differences were explained by proximity to major sources. Species differences arise from differences in macro and micro morphology of the above surface biomass. The study finds that the grasses, A. stolonifera and E rubra, are more effective than P. lanceolata and S. album at PM10 capture. Quantification of the annual PM10 removal potential was calculated under a maximum sedum green roof installation scenario for an area of the city centre, which totals 325 ha. Remediation of 2.3% (+/- 0.1%) of 9.18 tonnes PM10 inputs for this area could be achieved under this scenario. (C) 2012 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据