Literature DB >> 16996198

Estimating the reduction of urban PM10 concentrations by trees within an environmental information system for planners.

W J Bealey1, A G McDonald, E Nemitz, R Donovan, U Dragosits, T R Duffy, D Fowler.   

Abstract

Trees have been widely quoted as effective scavengers of both gaseous and particulate pollutants from the atmosphere. Recent work on the deposition of urban aerosols onto woodland allows the effect of tree planting strategies on airborne aerosol concentrations to be quantified and considered within the planning process. By identifying the potential planting locations in the local authority area, and applying them within a dispersion and deposition model, the potential magnitude of reduction in the ambient concentration of PM(10), achievable through urban tree planting, has been quantified for two UK cities. As part of the Environmental Information Systems for Planners (EISP), flow diagrams, based on planning decisions, have incorporated output from the model to make decisions on land use planning ranging from development plans and strategic planning, to development control. In this way, for any new developments that contribute to the local PM(10) level, the mitigation by planting trees can be assessed, and in some cases, reductions can be sufficient to meet air quality objectives for PM(10).

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Year:  2006        PMID: 16996198     DOI: 10.1016/j.jenvman.2006.07.007

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  13 in total

1.  Simulation study of dispersion and removal of particulate matter from traffic by road-side vegetation barrier.

Authors:  Tobi Eniolu Morakinyo; Yun Fat Lam
Journal:  Environ Sci Pollut Res Int       Date:  2015-12-09       Impact factor: 4.223

2.  The role of behaviour in adaptive morphological evolution of African proboscideans.

Authors:  Adrian M Lister
Journal:  Nature       Date:  2013-06-26       Impact factor: 49.962

Review 3.  Linking ecosystem services and human health: the Eco-Health Relationship Browser.

Authors:  Laura E Jackson; Jessica Daniel; Betsy McCorkle; Alexandra Sears; Kathleen F Bush
Journal:  Int J Public Health       Date:  2013-07-23       Impact factor: 3.380

4.  Developing Community-Level Policy and Practice to Reduce Traffic-Related Air Pollution Exposure.

Authors:  Doug Brugge; Allison P Patton; Alex Bob; Ellin Reisner; Lydia Lowe; Oliver-John M Bright; John L Durant; Jim Newman; Wig Zamore
Journal:  Environ Justice       Date:  2015-06-15

Review 5.  Green Infrastructure, Ecosystem Services, and Human Health.

Authors:  Christopher Coutts; Micah Hahn
Journal:  Int J Environ Res Public Health       Date:  2015-08-18       Impact factor: 3.390

6.  Is Neighborhood Green Space Protective against Associations between Child Asthma, Neighborhood Traffic Volume and Perceived Lack of Area Safety? Multilevel Analysis of 4447 Australian Children.

Authors:  Xiaoqi Feng; Thomas Astell-Burt
Journal:  Int J Environ Res Public Health       Date:  2017-05-19       Impact factor: 3.390

7.  Phyllostachys edulis forest reduces atmospheric PM2.5 and PAHs on hazy days at suburban area.

Authors:  Yu Fang Bi; Fei Yan Guo; Liu Yang; Hao Zhong; An Ke Wang; Yu Kui Wang; Zhi Zhuang Wu; Xu Hua Du
Journal:  Sci Rep       Date:  2018-08-22       Impact factor: 4.379

8.  Measuring and Quantifying Impacts of Environmental Parameters on Airborne Particulate Matter in Under-Viaducts Spaces in Wuhan, China.

Authors:  Lihua Yin; Tian Hang; Fanfan Qin; Xueting Lin; Yiwen Han
Journal:  Int J Environ Res Public Health       Date:  2021-05-13       Impact factor: 3.390

9.  Urban tree canopy and asthma, wheeze, rhinitis, and allergic sensitization to tree pollen in a New York City birth cohort.

Authors:  Gina S Lovasi; Jarlath P M O'Neil-Dunne; Jacqueline W T Lu; Daniel Sheehan; Matthew S Perzanowski; Sean W Macfaden; Kristen L King; Thomas Matte; Rachel L Miller; Lori A Hoepner; Frederica P Perera; Andrew Rundle
Journal:  Environ Health Perspect       Date:  2013-01-15       Impact factor: 9.031

10.  Using machine learning to investigate self-medication purchasing in England via high street retailer loyalty card data.

Authors:  Alec Davies; Mark A Green; Alex D Singleton
Journal:  PLoS One       Date:  2018-11-19       Impact factor: 3.240

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