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作者

Vít Kašpar;Miloš Zapletal;Pavel Samec;Jan Komárek;Jiří Bílek;Stanislav Juráň

来源

URBAN FORESTRY & URBAN GREENING,Vol.78,Issue1,Article 127757

语言

英文

关键字

作者单位

Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, Praha, Suchdol 165 00, Czech Republic;Silesian University in Opava, Institute of Physics in Opava, Bezručovo náměstí 1150/13, CZ-746 01 Opava, Czech Republic;Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, CZ-603 00 Brno, Czech Republic;Department of Geology and Soil Science, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, CZ-613 00 Brno, Czech Republic;Institute of Environmental Technology, Energy and Environmental Technology Centre, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 708 00 Ostrava, Czech Republic;Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, Praha, Suchdol 165 00, Czech Republic;Silesian University in Opava, Institute of Physics in Opava, Bezručovo náměstí 1150/13, CZ-746 01 Opava, Czech Republic;Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, CZ-603 00 Brno, Czech Republic;Department of Geology and Soil Science, Faculty of Forestry and Wood Technology, Mendel University in Brno, Zemědělská 3, CZ-613 00 Brno, Czech Republic;Institute of Environmental Technology, Energy and Environmental Technology Centre, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 708 00 Ostrava, Czech Republic

摘要

Urban greenery plays an important role in reducing air pollution, being one of the often-used, nature-based measures in sustainable and climate-resilient urban development. However, when modelling its effect on air pollution removal by dry deposition, coarse and time-limited data on vegetation properties are often included, disregarding the high spatial and temporal heterogeneity in urban forest canopies. Here, we present a detailed, physics-based approach for modelling particulate matter (PM10) and tropospheric ozone (O3) removal by urban greenery on a small scale that eliminates these constraints. Our procedure combines a dense network of low-cost optical and electrochemical air pollution sensors, and a remote sensing method for greenery structure monitoring derived from Unmanned aerial systems (UAS) imagery processed by the Structure from Motion (SfM) algorithm. This approach enabled the quantification of species- and individual-specific air pollution removal rates by woody plants throughout the growing season, exploring the high spatial and temporal variability of modelled removal rates within an urban forest. The total PM10 and O3 removal rates ranged from 7.6 g m-2 (PM10) and 12.6 g m-2 (O3) for mature trees of Acer pseudoplatanus to 0.1 g m-2 and 0.1 g m-2 for newly planted tree saplings of Salix daphnoides. The present study demonstrates that UAS-SfM can detect differences in structures among and within canopies and by involving these characteristics, they can shift the modelling of air pollution removal towards a level of individual woody plants and beyond, enabling more realistic and accurate quantification of air pollution removal. Moreover, this approach can be similarly applied when modelling other ecosystem services provided by urban greenery.