12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > Development and application of an urban tree ai...
View graph of relations

« Back

Development and application of an urban tree air quality score for photochemical pollution episodes using the Birmingham, United Kingdom, area as a case study

Research output: Contribution to journalJournal article

Published

Journal publication date2005
JournalEnvironmental Science and Technology
Journal number17
Volume39
Number of pages9
Pages6730-6738
Original languageEnglish

Abstract

An atmospheric chemistry model (CiTTyCAT) is used to quantify the effects of trees on urban air quality in scenarios of high photochemical pollution. The combined effects of both pollutant deposition to and emission of biogenic volatile organic compounds (BVOC) from the urban forest are considered, and the West Midlands, metropolitan area in the UK is used as a case study. While all trees can be beneficial to air quality in terms of the deposition of O-3, NO2, CO, and HNO3, some trees have the potential to contribute to the formation of O-3 due to the reaction of BVOC and NOx. A number of model scenarios are used to develop an urban tree air quality score (UTAQS) that ranks trees in order of their potential to improve air quality. Of the 30 species considered, pine, larch, and silver birch have the greatest potential to improve urban air quality, while oaks, willows, and poplars can worsen downwind air quality if planted in very large numbers. The UTAQS classification is designed with practitioners in mind, to help them achieve sustainable urban air quality. The UTAQS classification is applicable to all urban areas of the UK and other mid-latitude, temperate climate zones that have tree species common to those found in UK urban areas. The modeling approach used here is directly applicable to all areas of the world given the appropriate input data. It provides a tool that can help to achieve future sustainable urban air quality.